shivaam commented on code in PR #64274:
URL: https://github.com/apache/airflow/pull/64274#discussion_r3283085275


##########
providers/amazon/src/airflow/providers/amazon/aws/hooks/neptune_analytics.py:
##########
@@ -0,0 +1,37 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+from __future__ import annotations
+
+from airflow.providers.amazon.aws.hooks.base_aws import AwsBaseHook
+
+
+class NeptuneAnalyticsHook(AwsBaseHook):
+    """
+    Interact with Amazon Neptune Analytics.
+
+    Additional arguments (such as ``aws_conn_id``) may be specified and
+    are passed down to the underlying AwsBaseHook.
+
+    .. seealso::
+        - :class:`~airflow.providers.amazon.aws.hooks.base_aws.AwsBaseHook`
+    """
+
+    def __init__(self, *args, **kwargs):
+        kwargs["client_type"] = "neptune-graph"

Review Comment:
   difference between neptune graph vs neptune analytics?



##########
airflow-core/src/airflow/migrations/versions/0113_3_3_0_add_retry_policy_fields_to_ti.py:
##########
@@ -30,7 +30,7 @@
 is a metadata-only operation (no table rewrite).
 
 Revision ID: b8f3e4a1d2c9
-Revises: 9fabad868fdb
+Revises: fde9ed84d07b
 Create Date: 2026-04-16 12:00:00.000000

Review Comment:
   Is this expected?



##########
providers/amazon/tests/system/amazon/aws/example_neptune_analytics.py:
##########
@@ -0,0 +1,335 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from __future__ import annotations
+
+import contextlib
+import json
+import time
+from datetime import datetime
+
+import boto3
+
+from airflow.providers.amazon.aws.hooks.neptune_analytics import 
NeptuneAnalyticsHook
+from airflow.providers.amazon.aws.operators.neptune_analytics import (
+    NeptuneCancelImportTaskOperator,
+    NeptuneCreateGraphOperator,
+    NeptuneCreateGraphWithImportOperator,
+    NeptuneCreatePrivateGraphEndpointOperator,
+    NeptuneDeleteGraphOperator,
+    NeptuneDeletePrivateGraphEndpointOperator,
+    NeptuneStartImportTaskOperator,
+)
+from airflow.providers.amazon.aws.operators.s3 import (
+    S3CreateBucketOperator,
+    S3CreateObjectOperator,
+    S3DeleteBucketOperator,
+)
+from airflow.providers.common.compat.sdk import DAG, chain, task
+
+try:
+    from airflow.sdk import TriggerRule
+except ImportError:
+    # Compatibility for Airflow < 3.1
+    from airflow.utils.trigger_rule import TriggerRule  # type: 
ignore[no-redef,attr-defined]
+
+from system.amazon.aws.utils import SystemTestContextBuilder
+
+DAG_ID = "example_neptune_analytics"
+
+ROLE_ARN_KEY = "ROLE_ARN"
+
+sys_test_context_task = 
SystemTestContextBuilder().add_variable(ROLE_ARN_KEY).build()
+
+# Minimal OpenCypher CSV data for import testing.
+NODES_CSV = """~id,~label,name:String
+n1,Person,Alice
+n2,Person,Bob
+"""
+
+EDGES_CSV = """~id,~from,~to,~label
+e1,n1,n2,KNOWS
+"""
+
+NEPTUNE_ANALYTICS_TRUST_POLICY = json.dumps(
+    {
+        "Version": "2012-10-17",
+        "Statement": [
+            {
+                "Effect": "Allow",
+                "Principal": {"Service": "neptune-graph.amazonaws.com"},
+                "Action": "sts:AssumeRole",
+            }
+        ],
+    }
+)
+
+S3_READ_POLICY_DOCUMENT = json.dumps(
+    {
+        "Version": "2012-10-17",
+        "Statement": [
+            {
+                "Effect": "Allow",
+                "Action": ["s3:GetObject", "s3:ListBucket"],
+                "Resource": ["arn:aws:s3:::*", "arn:aws:s3:::*/*"],
+            }
+        ],
+    }
+)
+
+
+@task
+def create_neptune_import_role(role_name: str) -> str:
+    iam_client = boto3.client("iam")
+    iam_client.create_role(
+        RoleName=role_name,
+        AssumeRolePolicyDocument=NEPTUNE_ANALYTICS_TRUST_POLICY,
+        Description="Role for Neptune Analytics import system test",
+    )
+    iam_client.put_role_policy(
+        RoleName=role_name,
+        PolicyName="NeptuneAnalyticsS3Access",
+        PolicyDocument=S3_READ_POLICY_DOCUMENT,
+    )
+    role = iam_client.get_role(RoleName=role_name)
+    time.sleep(60)  # Wait for IAM eventual consistency (role + inline policy 
propagation)
+    return role["Role"]["Arn"]
+
+
+@task(trigger_rule=TriggerRule.ALL_DONE)
+def delete_neptune_import_role(role_name: str) -> None:
+    iam_client = boto3.client("iam")
+    with contextlib.suppress(iam_client.exceptions.NoSuchEntityException):
+        iam_client.delete_role_policy(RoleName=role_name, 
PolicyName="NeptuneAnalyticsS3Access")

Review Comment:
   only deleting the policy not the role



##########
providers/amazon/tests/system/amazon/aws/example_neptune_analytics.py:
##########
@@ -0,0 +1,335 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from __future__ import annotations
+
+import contextlib
+import json
+import time
+from datetime import datetime
+
+import boto3
+
+from airflow.providers.amazon.aws.hooks.neptune_analytics import 
NeptuneAnalyticsHook
+from airflow.providers.amazon.aws.operators.neptune_analytics import (
+    NeptuneCancelImportTaskOperator,
+    NeptuneCreateGraphOperator,
+    NeptuneCreateGraphWithImportOperator,
+    NeptuneCreatePrivateGraphEndpointOperator,
+    NeptuneDeleteGraphOperator,
+    NeptuneDeletePrivateGraphEndpointOperator,
+    NeptuneStartImportTaskOperator,
+)
+from airflow.providers.amazon.aws.operators.s3 import (
+    S3CreateBucketOperator,
+    S3CreateObjectOperator,
+    S3DeleteBucketOperator,
+)
+from airflow.providers.common.compat.sdk import DAG, chain, task
+
+try:
+    from airflow.sdk import TriggerRule
+except ImportError:
+    # Compatibility for Airflow < 3.1
+    from airflow.utils.trigger_rule import TriggerRule  # type: 
ignore[no-redef,attr-defined]
+
+from system.amazon.aws.utils import SystemTestContextBuilder
+
+DAG_ID = "example_neptune_analytics"
+
+ROLE_ARN_KEY = "ROLE_ARN"
+
+sys_test_context_task = 
SystemTestContextBuilder().add_variable(ROLE_ARN_KEY).build()
+
+# Minimal OpenCypher CSV data for import testing.
+NODES_CSV = """~id,~label,name:String
+n1,Person,Alice
+n2,Person,Bob
+"""
+
+EDGES_CSV = """~id,~from,~to,~label
+e1,n1,n2,KNOWS
+"""
+
+NEPTUNE_ANALYTICS_TRUST_POLICY = json.dumps(
+    {
+        "Version": "2012-10-17",
+        "Statement": [
+            {
+                "Effect": "Allow",
+                "Principal": {"Service": "neptune-graph.amazonaws.com"},
+                "Action": "sts:AssumeRole",
+            }
+        ],
+    }
+)
+
+S3_READ_POLICY_DOCUMENT = json.dumps(
+    {
+        "Version": "2012-10-17",
+        "Statement": [
+            {
+                "Effect": "Allow",
+                "Action": ["s3:GetObject", "s3:ListBucket"],
+                "Resource": ["arn:aws:s3:::*", "arn:aws:s3:::*/*"],
+            }
+        ],
+    }
+)
+
+
+@task
+def create_neptune_import_role(role_name: str) -> str:
+    iam_client = boto3.client("iam")
+    iam_client.create_role(
+        RoleName=role_name,
+        AssumeRolePolicyDocument=NEPTUNE_ANALYTICS_TRUST_POLICY,
+        Description="Role for Neptune Analytics import system test",
+    )
+    iam_client.put_role_policy(
+        RoleName=role_name,
+        PolicyName="NeptuneAnalyticsS3Access",
+        PolicyDocument=S3_READ_POLICY_DOCUMENT,
+    )
+    role = iam_client.get_role(RoleName=role_name)
+    time.sleep(60)  # Wait for IAM eventual consistency (role + inline policy 
propagation)
+    return role["Role"]["Arn"]
+
+
+@task(trigger_rule=TriggerRule.ALL_DONE)
+def delete_neptune_import_role(role_name: str) -> None:
+    iam_client = boto3.client("iam")
+    with contextlib.suppress(iam_client.exceptions.NoSuchEntityException):
+        iam_client.delete_role_policy(RoleName=role_name, 
PolicyName="NeptuneAnalyticsS3Access")
+
+
+@task(trigger_rule=TriggerRule.ALL_DONE)
+def delete_graph_if_exists(graph_name: str) -> None:
+    """Safety net to clean up the graph in case a previous task failed."""
+    hook = NeptuneAnalyticsHook()
+    with contextlib.suppress(Exception):
+        # List graphs and find by name
+        paginator = hook.conn.get_paginator("list_graphs")
+        for page in paginator.paginate():
+            for graph in page.get("graphs", []):
+                if graph.get("name") == graph_name:
+                    graph_id = graph["id"]
+                    # Disable deletion protection if enabled
+
+                    hook.conn.update_graph(graphIdentifier=graph_id, 
deletionProtection=False)
+
+                    hook.conn.delete_graph(graphIdentifier=graph_id, 
skipSnapshot=True)
+                    hook.conn.get_waiter("graph_deleted").wait(
+                        graphIdentifier=graph_id,
+                        WaiterConfig={"Delay": 30, "MaxAttempts": 60},
+                    )
+                    return
+
+
+with DAG(
+    dag_id=DAG_ID,
+    schedule="@once",
+    start_date=datetime(2021, 1, 1),
+    catchup=False,
+) as dag:
+    test_context = sys_test_context_task()
+
+    env_id = test_context["ENV_ID"]
+    graph_name = f"{env_id}-graph"
+    import_graph_name = f"{env_id}-import-graph"
+    bucket_name = f"{env_id}-neptune-analytics"
+    import_role_name = f"{env_id}-neptune-import"
+    region = boto3.session.Session().region_name
+
+    # --- TEST SETUP ---
+
+    create_bucket = S3CreateBucketOperator(
+        task_id="create_bucket",
+        bucket_name=bucket_name,
+    )
+
+    upload_nodes = S3CreateObjectOperator(
+        task_id="upload_nodes",
+        s3_bucket=bucket_name,
+        s3_key="data/nodes.csv",
+        data=NODES_CSV,
+        replace=True,
+    )
+
+    upload_edges = S3CreateObjectOperator(
+        task_id="upload_edges",
+        s3_bucket=bucket_name,
+        s3_key="data/edges.csv",
+        data=EDGES_CSV,
+        replace=True,
+    )
+
+    create_role = create_neptune_import_role(import_role_name)
+
+    # --- TEST BODY ---
+
+    # [START howto_operator_neptune_analytics_create_graph]
+    create_graph = NeptuneCreateGraphOperator(
+        task_id="create_graph",
+        graph_name=graph_name,
+        vector_search_config={"dimension": 128},
+        provisioned_memory=32,
+        public_connectivity=True,
+        replica_count=0,
+        deletion_protection=False,
+        wait_for_completion=True,
+        deferrable=False,
+        waiter_delay=30,
+        waiter_max_attempts=60,
+    )
+    # [END howto_operator_neptune_analytics_create_graph]
+
+    # [START howto_operator_neptune_analytics_create_private_endpoint]
+    create_endpoint = NeptuneCreatePrivateGraphEndpointOperator(
+        task_id="create_endpoint",
+        graph_identifier="{{ 
ti.xcom_pull(task_ids='create_graph')['graph_id']}}",
+        wait_for_completion=True,
+    )
+    # [END howto_operator_neptune_analytics_create_private_endpoint]
+
+    # [START howto_operator_neptune_analytics_delete_private_endpoint]
+    delete_endpoint = NeptuneDeletePrivateGraphEndpointOperator(
+        task_id="delete_endpoint",
+        graph_identifier="{{ ti.xcom_pull(task_ids='create_graph')['graph_id'] 
}}",
+        vpc_id="{{ ti.xcom_pull(task_ids='create_endpoint')['vpc_id'] }}",
+        wait_for_completion=True,
+        deferrable=False,
+        waiter_delay=30,
+        waiter_max_attempts=60,
+    )
+    # [END howto_operator_neptune_analytics_delete_private_endpoint]
+
+    # [START howto_operator_neptune_analytics_start_import_task]
+    start_import = NeptuneStartImportTaskOperator(
+        task_id="start_import",
+        graph_identifier="{{ ti.xcom_pull(task_ids='create_graph')['graph_id'] 
}}",
+        role_arn=create_role,
+        source=f"s3://{bucket_name}/data/",
+        format="CSV",
+        fail_on_error=True,
+        wait_for_completion=True,
+        deferrable=False,
+        waiter_delay=30,
+        waiter_max_attempts=60,
+    )
+    # [END howto_operator_neptune_analytics_start_import_task]
+
+    # [START howto_operator_neptune_analytics_cancel_import_task]
+    cancel_import = NeptuneCancelImportTaskOperator(

Review Comment:
   wait_for_completion=True on start_import makes cancel_import impossible and 
by the time the cancel runs, the import is already SUCCEEDED and AWS returns 
ConflictException: Import task ... has completed and cannot be canceled.
   
   Set this to wait_for_completion=False so cancel_import races a still-running 
task. Note the 2-row CSV completes in seconds even then, so consider a larger 
source (or accepting SUCCEEDED as a valid terminal state in the cancel waiter) 
to avoid an intermittent race on slow runners.



##########
providers/amazon/tests/system/amazon/aws/example_neptune_analytics.py:
##########
@@ -0,0 +1,335 @@
+# Licensed to the Apache Software Foundation (ASF) under one

Review Comment:
   Ran the system test against real AWS (us-west-2). Graph create, endpoint 
create, and import all worked. Two issues blocked the run from passing:
   
   1. cancel_import always fails — start_import.wait_for_completion=True means 
the import is already SUCCEEDED when cancel runs (ConflictException: ... has 
completed and cannot be canceled).
   
   2. Cleanup leaked a graph + VPC endpoint + IAM role: the 
delete_graph_if_exists safety net tries DeleteGraph without first deleting the 
attached private endpoint, and with contextlib.suppress(Exception): hides the 
resulting ConflictException. delete_neptune_import_role only deletes the inline 
policy, never the role itself. Had to clean up manually. 



##########
providers/amazon/src/airflow/providers/amazon/aws/operators/neptune_analytics.py:
##########
@@ -0,0 +1,1006 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from __future__ import annotations
+
+from collections.abc import Sequence
+from typing import TYPE_CHECKING, Any
+
+from botocore.exceptions import ClientError
+
+from airflow.providers.amazon.aws.hooks.neptune_analytics import 
NeptuneAnalyticsHook
+from airflow.providers.amazon.aws.links.ec2 import VpcEndpointLink
+from airflow.providers.amazon.aws.links.neptune_analytics import 
NeptuneGraphLink, NeptuneImportTaskLink
+from airflow.providers.amazon.aws.operators.base_aws import AwsBaseOperator
+from airflow.providers.amazon.aws.triggers.neptune_analytics import (
+    NeptuneGraphAvailableTrigger,
+    NeptuneGraphDeletedTrigger,
+    NeptuneGraphPrivateEndpointAvailableTrigger,
+    NeptuneGraphPrivateEndpointDeletedTrigger,
+    NeptuneImportTaskCancelledTrigger,
+    NeptuneImportTaskCompleteTrigger,
+)
+from airflow.providers.amazon.aws.utils.mixins import aws_template_fields
+from airflow.providers.common.compat.sdk import conf
+
+if TYPE_CHECKING:
+    from airflow.sdk import Context
+
+from airflow.providers.amazon.aws.exceptions import (
+    NeptuneGraphCreationFailedError,
+    NeptuneGraphDeletionFailedError,
+    NeptuneImportTaskCancellationFailedError,
+    NeptunePrivateEndpointCreationFailedError,
+    NeptunePrivateEndpointDeletionFailedError,
+)
+
+
+class NeptuneCreateGraphOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Creates an empty Amazon Neptune Graph database.
+
+    Neptune Analytics is a memory-optimized graph database engine for 
analytics. With Neptune Analytics, you can get insights and find trends by 
processing large amounts of graph data in seconds.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneCreateGraphOperator`
+
+    :param graph_name: Name of Neptune graph to create
+    :param vector_search_config: Specifies the number of dimensions for vector 
embeddings that will be loaded into the graph.
+    :param provisioned_memory: The provisioned memory-optimized Neptune 
Capacity Units (m-NCUs) to use for the graph.
+    :param public_connectivity: Specifies whether or not the graph can be 
reachable over the internet.
+    :param replica_count: The number of replicas in other AZs.
+    :param deletion_protection:  Indicates whether or not to enable deletion 
protection on the graph.
+        The graph can't be deleted when deletion protection is enabled.
+    :param kms_key_id:  Specifies a KMS key to use to encrypt data in the new 
graph.
+    :param tags: Specifies metadata tags to add to the graph.
+    :param wait_for_completion: Whether to wait for the graph to start. 
(default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
graph to start.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields(
+        "graph_name", "vector_search_config", "provisioned_memory"
+    )
+
+    template_fields_renderers = {
+        "vector_search_config": "json",
+    }
+
+    operator_extra_links = (NeptuneGraphLink(),)
+
+    def __init__(
+        self,
+        graph_name: str,
+        vector_search_config: dict,
+        provisioned_memory: int,
+        public_connectivity: bool | None = None,
+        replica_count: int | None = None,
+        deletion_protection: bool = False,
+        kms_key_id: str | None = None,
+        tags: dict | None = None,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_name = graph_name
+        self.vector_search_config = vector_search_config
+        self.replica_count = replica_count
+        self.provisioned_memory = provisioned_memory
+        self.public_connectivity = public_connectivity
+        self.deletion_protect = deletion_protection
+        self.kms_key = kms_key_id
+        self.tags = tags
+        self.wait_for_completion = wait_for_completion
+        self.deferrable = deferrable
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+
+    def execute(self, context: Context) -> dict:
+        self.log.info("Creating graph %s", self.graph_name)
+
+        create_params = {
+            "graphName": self.graph_name,
+            "vectorSearchConfiguration": self.vector_search_config,
+            "provisionedMemory": self.provisioned_memory,
+            **{
+                k: v
+                for k, v in {
+                    "replicaCount": self.replica_count,
+                    "publicConnectivity": self.public_connectivity,
+                    "deletionProtection": self.deletion_protect,
+                    "kmsKeyIdentifier": self.kms_key,
+                    "tags": self.tags,
+                }.items()
+                if v is not None
+            },
+        }
+
+        response = self.hook.conn.create_graph(**create_params)
+
+        self.log.info("Graph %s in status %s", self.graph_name, 
response.get("status", "Unknown"))
+        self.graph_id = response.get("id", None)
+
+        graph_url = NeptuneGraphLink.format_str.format(
+            graph_id=self.graph_id,
+            
aws_domain=NeptuneGraphLink.get_aws_domain(self.hook.conn_partition),
+            region_name=self.hook.conn_region_name,
+        )
+
+        NeptuneGraphLink.persist(
+            context=context,
+            operator=self,
+            region_name=self.hook.conn_region_name,
+            aws_partition=self.hook.conn_partition,
+            graph_id=self.graph_id,
+        )
+        self.log.info("You can view this Neptune Graph at : %s", graph_url)
+
+        if self.deferrable:
+            self.log.info("Deferring until graph %s is available", 
self.graph_id)
+            self.defer(
+                trigger=NeptuneGraphAvailableTrigger(
+                    aws_conn_id=self.aws_conn_id,
+                    graph_id=self.graph_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                ),
+                method_name="execute_complete",
+            )
+
+        if self.wait_for_completion:
+            self.log.info("Waiting until graph %s is available", self.graph_id)
+            self.hook.get_waiter("graph_available").wait(
+                graphIdentifier=self.graph_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+
+        return {"graph_id": self.graph_id}
+
+    def execute_complete(self, context: Context, event: dict[str, Any] | None 
= None) -> dict[str, Any]:
+        if event is None:
+            raise NeptuneGraphCreationFailedError(
+                "No event received while waiting for Neptune graph creation to 
complete."
+            )
+
+        if event.get("status") != "success":
+            raise NeptuneGraphCreationFailedError(
+                event.get(
+                    "message",
+                    f"Neptune graph {self.graph_id} creation did not complete 
successfully: {event}",
+                )
+            )
+
+        self.log.info("Neptune graph %s complete", self.graph_id)
+
+        return {"graph_id": self.graph_id}
+
+
+class 
NeptuneCreatePrivateGraphEndpointOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Creates a Neptune Graph private endpoint.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneCreatePrivateGraphEndpointOperator`
+
+    :param graph_identifier: Neptune Graph id
+    :param vpc_id: VPC to create endpoint in
+    :param subnet_ids: Subnets in which private graph endpoint ENIs are created
+    :param vpc_security_group_ids: Security groups to be attached to the 
private graph endpoint
+    :param wait_for_completion: Whether to wait for the endpoint to be 
available. (default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
endpoint to become available.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields(
+        "graph_identifier", "vpc_id", "subnet_ids", "vpc_security_group_ids"
+    )
+
+    def __init__(
+        self,
+        graph_identifier: str,
+        vpc_id: str | None = None,
+        subnet_ids: list[str] | None = None,
+        vpc_security_group_ids: list[str] | None = None,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_identifier = graph_identifier
+        self.vpc_id = vpc_id
+        self.subnet_ids = subnet_ids
+        self.vpc_security_group_ids = vpc_security_group_ids
+        self.wait_for_completion = wait_for_completion
+        self.deferrable = deferrable
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+
+    def execute(self, context: Context) -> dict:
+        self.log.info("Creating private endpoint for graph %s", 
self.graph_identifier)
+
+        create_params = {
+            "graphIdentifier": self.graph_identifier,
+            **{
+                k: v
+                for k, v in {
+                    "vpcId": self.vpc_id,
+                    "subnetIds": self.subnet_ids,
+                    "vpcSecurityGroupIds": self.vpc_security_group_ids,
+                }.items()
+                if v is not None
+            },
+        }
+
+        # create the endpoint
+
+        result = self.hook.conn.create_private_graph_endpoint(**create_params)
+        status = result.get("status", "Unknown")
+
+        self.log.info("Status of endpoint: %s", status)
+
+        if status in ["FAILED"]:
+            raise NeptunePrivateEndpointCreationFailedError(
+                f"Private endpoint failed to create for graph 
{self.graph_identifier}"
+            )
+
+        # if VPC not provided, use the one that is returned, which is the 
default VPC. Required for the waiter
+        self.vpc_id = result.get("vpcId", self.vpc_id)
+
+        if self.deferrable:
+            self.log.info("Deferring until endpoint is available")
+            self.defer(

Review Comment:
   self.defer() on line 298 raises TaskDeferred, so every line from there to 
the return is unreachable in deferrable mode — including this persist() call. 
Users running with deferrable=True won't see the VPC Endpoint link in the UI. 
Move the persist (and endpoint_url log line) above the defer block, using 
result["vpcEndpointId"] which is already available from the 
create_private_graph_endpoint response. NeptuneCreateGraphOperator already 
follows this pattern at line ~165.



##########
providers/amazon/tests/unit/amazon/aws/hooks/test_neptune_analytics.py:
##########
@@ -0,0 +1,46 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from __future__ import annotations
+
+from collections.abc import Generator
+from unittest import mock
+
+import pytest
+from moto import mock_aws
+
+from airflow.providers.amazon.aws.hooks.neptune_analytics import 
NeptuneAnalyticsHook
+
+
[email protected]
+def neptune_hook() -> Generator[NeptuneAnalyticsHook, None, None]:
+    """Returns a NeptuneAnalyticsHook mocked with moto"""
+    with mock_aws():
+        yield NeptuneAnalyticsHook(aws_conn_id="aws_default")
+
+
+class TestNeptuneAnalyticsHook:
+    graph_id = "abc123"
+
+    def test_get_conn_returns_a_boto3_connection(self):
+        hook = NeptuneAnalyticsHook(aws_conn_id="aws_default")
+        assert hook.get_conn() is not None
+
+    @mock.patch.object(NeptuneAnalyticsHook, "get_waiter")
+    def test_wait_for_graph_availability(self, mock_get_waiter, neptune_hook: 
NeptuneAnalyticsHook):
+        waiter = mock_get_waiter("graph_available")

Review Comment:
   you can potentially assert if the client name here. Not sure if this test 
adds any value. 



##########
providers/amazon/src/airflow/providers/amazon/aws/operators/neptune_analytics.py:
##########
@@ -0,0 +1,1006 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from __future__ import annotations
+
+from collections.abc import Sequence
+from typing import TYPE_CHECKING, Any
+
+from botocore.exceptions import ClientError
+
+from airflow.providers.amazon.aws.hooks.neptune_analytics import 
NeptuneAnalyticsHook
+from airflow.providers.amazon.aws.links.ec2 import VpcEndpointLink
+from airflow.providers.amazon.aws.links.neptune_analytics import 
NeptuneGraphLink, NeptuneImportTaskLink
+from airflow.providers.amazon.aws.operators.base_aws import AwsBaseOperator
+from airflow.providers.amazon.aws.triggers.neptune_analytics import (
+    NeptuneGraphAvailableTrigger,
+    NeptuneGraphDeletedTrigger,
+    NeptuneGraphPrivateEndpointAvailableTrigger,
+    NeptuneGraphPrivateEndpointDeletedTrigger,
+    NeptuneImportTaskCancelledTrigger,
+    NeptuneImportTaskCompleteTrigger,
+)
+from airflow.providers.amazon.aws.utils.mixins import aws_template_fields
+from airflow.providers.common.compat.sdk import conf
+
+if TYPE_CHECKING:
+    from airflow.sdk import Context
+
+from airflow.providers.amazon.aws.exceptions import (
+    NeptuneGraphCreationFailedError,
+    NeptuneGraphDeletionFailedError,
+    NeptuneImportTaskCancellationFailedError,
+    NeptunePrivateEndpointCreationFailedError,
+    NeptunePrivateEndpointDeletionFailedError,
+)
+
+
+class NeptuneCreateGraphOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Creates an empty Amazon Neptune Graph database.
+
+    Neptune Analytics is a memory-optimized graph database engine for 
analytics. With Neptune Analytics, you can get insights and find trends by 
processing large amounts of graph data in seconds.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneCreateGraphOperator`
+
+    :param graph_name: Name of Neptune graph to create
+    :param vector_search_config: Specifies the number of dimensions for vector 
embeddings that will be loaded into the graph.
+    :param provisioned_memory: The provisioned memory-optimized Neptune 
Capacity Units (m-NCUs) to use for the graph.
+    :param public_connectivity: Specifies whether or not the graph can be 
reachable over the internet.
+    :param replica_count: The number of replicas in other AZs.
+    :param deletion_protection:  Indicates whether or not to enable deletion 
protection on the graph.
+        The graph can't be deleted when deletion protection is enabled.
+    :param kms_key_id:  Specifies a KMS key to use to encrypt data in the new 
graph.
+    :param tags: Specifies metadata tags to add to the graph.
+    :param wait_for_completion: Whether to wait for the graph to start. 
(default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
graph to start.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields(
+        "graph_name", "vector_search_config", "provisioned_memory"
+    )
+
+    template_fields_renderers = {
+        "vector_search_config": "json",
+    }
+
+    operator_extra_links = (NeptuneGraphLink(),)
+
+    def __init__(
+        self,
+        graph_name: str,
+        vector_search_config: dict,
+        provisioned_memory: int,
+        public_connectivity: bool | None = None,
+        replica_count: int | None = None,
+        deletion_protection: bool = False,
+        kms_key_id: str | None = None,
+        tags: dict | None = None,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_name = graph_name
+        self.vector_search_config = vector_search_config
+        self.replica_count = replica_count
+        self.provisioned_memory = provisioned_memory
+        self.public_connectivity = public_connectivity
+        self.deletion_protect = deletion_protection
+        self.kms_key = kms_key_id
+        self.tags = tags
+        self.wait_for_completion = wait_for_completion
+        self.deferrable = deferrable
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+
+    def execute(self, context: Context) -> dict:
+        self.log.info("Creating graph %s", self.graph_name)
+
+        create_params = {
+            "graphName": self.graph_name,
+            "vectorSearchConfiguration": self.vector_search_config,
+            "provisionedMemory": self.provisioned_memory,
+            **{
+                k: v
+                for k, v in {
+                    "replicaCount": self.replica_count,
+                    "publicConnectivity": self.public_connectivity,
+                    "deletionProtection": self.deletion_protect,
+                    "kmsKeyIdentifier": self.kms_key,
+                    "tags": self.tags,
+                }.items()
+                if v is not None
+            },
+        }
+
+        response = self.hook.conn.create_graph(**create_params)
+
+        self.log.info("Graph %s in status %s", self.graph_name, 
response.get("status", "Unknown"))
+        self.graph_id = response.get("id", None)
+
+        graph_url = NeptuneGraphLink.format_str.format(
+            graph_id=self.graph_id,
+            
aws_domain=NeptuneGraphLink.get_aws_domain(self.hook.conn_partition),
+            region_name=self.hook.conn_region_name,
+        )
+
+        NeptuneGraphLink.persist(
+            context=context,
+            operator=self,
+            region_name=self.hook.conn_region_name,
+            aws_partition=self.hook.conn_partition,
+            graph_id=self.graph_id,
+        )
+        self.log.info("You can view this Neptune Graph at : %s", graph_url)
+
+        if self.deferrable:
+            self.log.info("Deferring until graph %s is available", 
self.graph_id)
+            self.defer(
+                trigger=NeptuneGraphAvailableTrigger(
+                    aws_conn_id=self.aws_conn_id,
+                    graph_id=self.graph_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                ),
+                method_name="execute_complete",
+            )
+
+        if self.wait_for_completion:
+            self.log.info("Waiting until graph %s is available", self.graph_id)
+            self.hook.get_waiter("graph_available").wait(
+                graphIdentifier=self.graph_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+
+        return {"graph_id": self.graph_id}
+
+    def execute_complete(self, context: Context, event: dict[str, Any] | None 
= None) -> dict[str, Any]:
+        if event is None:
+            raise NeptuneGraphCreationFailedError(
+                "No event received while waiting for Neptune graph creation to 
complete."
+            )
+
+        if event.get("status") != "success":
+            raise NeptuneGraphCreationFailedError(
+                event.get(
+                    "message",
+                    f"Neptune graph {self.graph_id} creation did not complete 
successfully: {event}",
+                )
+            )
+
+        self.log.info("Neptune graph %s complete", self.graph_id)

Review Comment:
   Other Amazon deferrable operators use validate_execute_complete_event(event) 
and pull identifiers from the event dict. I dont think we can use self.graph_id 
across the defer/resume boundary. Also, it is a good practice to keep all 
operators follow the same convention.



##########
providers/amazon/src/airflow/providers/amazon/aws/operators/neptune_analytics.py:
##########
@@ -0,0 +1,1006 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from __future__ import annotations
+
+from collections.abc import Sequence
+from typing import TYPE_CHECKING, Any
+
+from botocore.exceptions import ClientError
+
+from airflow.providers.amazon.aws.hooks.neptune_analytics import 
NeptuneAnalyticsHook
+from airflow.providers.amazon.aws.links.ec2 import VpcEndpointLink
+from airflow.providers.amazon.aws.links.neptune_analytics import 
NeptuneGraphLink, NeptuneImportTaskLink
+from airflow.providers.amazon.aws.operators.base_aws import AwsBaseOperator
+from airflow.providers.amazon.aws.triggers.neptune_analytics import (
+    NeptuneGraphAvailableTrigger,
+    NeptuneGraphDeletedTrigger,
+    NeptuneGraphPrivateEndpointAvailableTrigger,
+    NeptuneGraphPrivateEndpointDeletedTrigger,
+    NeptuneImportTaskCancelledTrigger,
+    NeptuneImportTaskCompleteTrigger,
+)
+from airflow.providers.amazon.aws.utils.mixins import aws_template_fields
+from airflow.providers.common.compat.sdk import conf
+
+if TYPE_CHECKING:
+    from airflow.sdk import Context
+
+from airflow.providers.amazon.aws.exceptions import (
+    NeptuneGraphCreationFailedError,
+    NeptuneGraphDeletionFailedError,
+    NeptuneImportTaskCancellationFailedError,
+    NeptunePrivateEndpointCreationFailedError,
+    NeptunePrivateEndpointDeletionFailedError,
+)
+
+
+class NeptuneCreateGraphOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Creates an empty Amazon Neptune Graph database.
+
+    Neptune Analytics is a memory-optimized graph database engine for 
analytics. With Neptune Analytics, you can get insights and find trends by 
processing large amounts of graph data in seconds.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneCreateGraphOperator`
+
+    :param graph_name: Name of Neptune graph to create
+    :param vector_search_config: Specifies the number of dimensions for vector 
embeddings that will be loaded into the graph.
+    :param provisioned_memory: The provisioned memory-optimized Neptune 
Capacity Units (m-NCUs) to use for the graph.
+    :param public_connectivity: Specifies whether or not the graph can be 
reachable over the internet.
+    :param replica_count: The number of replicas in other AZs.
+    :param deletion_protection:  Indicates whether or not to enable deletion 
protection on the graph.
+        The graph can't be deleted when deletion protection is enabled.
+    :param kms_key_id:  Specifies a KMS key to use to encrypt data in the new 
graph.
+    :param tags: Specifies metadata tags to add to the graph.
+    :param wait_for_completion: Whether to wait for the graph to start. 
(default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
graph to start.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields(
+        "graph_name", "vector_search_config", "provisioned_memory"
+    )
+
+    template_fields_renderers = {
+        "vector_search_config": "json",
+    }
+
+    operator_extra_links = (NeptuneGraphLink(),)
+
+    def __init__(
+        self,
+        graph_name: str,
+        vector_search_config: dict,
+        provisioned_memory: int,
+        public_connectivity: bool | None = None,
+        replica_count: int | None = None,
+        deletion_protection: bool = False,
+        kms_key_id: str | None = None,
+        tags: dict | None = None,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_name = graph_name
+        self.vector_search_config = vector_search_config
+        self.replica_count = replica_count
+        self.provisioned_memory = provisioned_memory
+        self.public_connectivity = public_connectivity
+        self.deletion_protect = deletion_protection
+        self.kms_key = kms_key_id
+        self.tags = tags
+        self.wait_for_completion = wait_for_completion
+        self.deferrable = deferrable
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+
+    def execute(self, context: Context) -> dict:
+        self.log.info("Creating graph %s", self.graph_name)
+
+        create_params = {
+            "graphName": self.graph_name,
+            "vectorSearchConfiguration": self.vector_search_config,
+            "provisionedMemory": self.provisioned_memory,
+            **{
+                k: v
+                for k, v in {
+                    "replicaCount": self.replica_count,
+                    "publicConnectivity": self.public_connectivity,
+                    "deletionProtection": self.deletion_protect,
+                    "kmsKeyIdentifier": self.kms_key,
+                    "tags": self.tags,
+                }.items()
+                if v is not None
+            },
+        }
+
+        response = self.hook.conn.create_graph(**create_params)
+
+        self.log.info("Graph %s in status %s", self.graph_name, 
response.get("status", "Unknown"))
+        self.graph_id = response.get("id", None)
+
+        graph_url = NeptuneGraphLink.format_str.format(
+            graph_id=self.graph_id,
+            
aws_domain=NeptuneGraphLink.get_aws_domain(self.hook.conn_partition),
+            region_name=self.hook.conn_region_name,
+        )
+
+        NeptuneGraphLink.persist(
+            context=context,
+            operator=self,
+            region_name=self.hook.conn_region_name,
+            aws_partition=self.hook.conn_partition,
+            graph_id=self.graph_id,
+        )
+        self.log.info("You can view this Neptune Graph at : %s", graph_url)
+
+        if self.deferrable:
+            self.log.info("Deferring until graph %s is available", 
self.graph_id)
+            self.defer(
+                trigger=NeptuneGraphAvailableTrigger(
+                    aws_conn_id=self.aws_conn_id,
+                    graph_id=self.graph_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                ),
+                method_name="execute_complete",
+            )
+
+        if self.wait_for_completion:
+            self.log.info("Waiting until graph %s is available", self.graph_id)
+            self.hook.get_waiter("graph_available").wait(
+                graphIdentifier=self.graph_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+
+        return {"graph_id": self.graph_id}
+
+    def execute_complete(self, context: Context, event: dict[str, Any] | None 
= None) -> dict[str, Any]:
+        if event is None:
+            raise NeptuneGraphCreationFailedError(
+                "No event received while waiting for Neptune graph creation to 
complete."
+            )
+
+        if event.get("status") != "success":
+            raise NeptuneGraphCreationFailedError(
+                event.get(
+                    "message",
+                    f"Neptune graph {self.graph_id} creation did not complete 
successfully: {event}",
+                )
+            )
+
+        self.log.info("Neptune graph %s complete", self.graph_id)
+
+        return {"graph_id": self.graph_id}
+
+
+class 
NeptuneCreatePrivateGraphEndpointOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Creates a Neptune Graph private endpoint.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneCreatePrivateGraphEndpointOperator`
+
+    :param graph_identifier: Neptune Graph id
+    :param vpc_id: VPC to create endpoint in
+    :param subnet_ids: Subnets in which private graph endpoint ENIs are created
+    :param vpc_security_group_ids: Security groups to be attached to the 
private graph endpoint
+    :param wait_for_completion: Whether to wait for the endpoint to be 
available. (default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
endpoint to become available.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields(
+        "graph_identifier", "vpc_id", "subnet_ids", "vpc_security_group_ids"
+    )
+
+    def __init__(
+        self,
+        graph_identifier: str,
+        vpc_id: str | None = None,
+        subnet_ids: list[str] | None = None,
+        vpc_security_group_ids: list[str] | None = None,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_identifier = graph_identifier
+        self.vpc_id = vpc_id
+        self.subnet_ids = subnet_ids
+        self.vpc_security_group_ids = vpc_security_group_ids
+        self.wait_for_completion = wait_for_completion
+        self.deferrable = deferrable
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+
+    def execute(self, context: Context) -> dict:
+        self.log.info("Creating private endpoint for graph %s", 
self.graph_identifier)
+
+        create_params = {
+            "graphIdentifier": self.graph_identifier,
+            **{
+                k: v
+                for k, v in {
+                    "vpcId": self.vpc_id,
+                    "subnetIds": self.subnet_ids,
+                    "vpcSecurityGroupIds": self.vpc_security_group_ids,
+                }.items()
+                if v is not None
+            },
+        }
+
+        # create the endpoint
+
+        result = self.hook.conn.create_private_graph_endpoint(**create_params)
+        status = result.get("status", "Unknown")
+
+        self.log.info("Status of endpoint: %s", status)
+
+        if status in ["FAILED"]:
+            raise NeptunePrivateEndpointCreationFailedError(
+                f"Private endpoint failed to create for graph 
{self.graph_identifier}"
+            )
+
+        # if VPC not provided, use the one that is returned, which is the 
default VPC. Required for the waiter
+        self.vpc_id = result.get("vpcId", self.vpc_id)
+
+        if self.deferrable:
+            self.log.info("Deferring until endpoint is available")
+            self.defer(
+                trigger=NeptuneGraphPrivateEndpointAvailableTrigger(
+                    aws_conn_id=self.aws_conn_id,
+                    graph_id=self.graph_identifier,
+                    vpc_id=self.vpc_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                ),
+                method_name="execute_complete",
+            )
+
+        if self.wait_for_completion:
+            self.log.info("Waiting until endpoint is available")
+            self.hook.get_waiter("private_graph_endpoint_available").wait(
+                graphIdentifier=self.graph_identifier,
+                vpcId=self.vpc_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+
+        endpoint_id = self._get_graph_endpoint_id()
+
+        endpoint_url = VpcEndpointLink.format_str.format(
+            endpoint_id=endpoint_id,
+            
aws_domain=VpcEndpointLink.get_aws_domain(self.hook.conn_partition),
+            region_name=self.hook.conn_region_name,
+        )
+
+        VpcEndpointLink.persist(
+            context=context,
+            operator=self,
+            region_name=self.hook.conn_region_name,
+            aws_partition=self.hook.conn_partition,
+            endpoint_id=endpoint_id,
+        )
+        self.log.info("You can view this private endpoint at : %s", 
endpoint_url)
+
+        return {"vpc_endpoint_id": endpoint_id, "graph_id": 
self.graph_identifier, "vpc_id": self.vpc_id}
+
+    def _get_graph_endpoint_id(self):
+        """Return the vpc endpoint id for this graph."""
+        result = self.hook.conn.get_private_graph_endpoint(
+            graphIdentifier=self.graph_identifier, vpcId=self.vpc_id
+        )
+        return result.get("vpcEndpointId")
+
+    def execute_complete(self, context: Context, event: dict[str, Any] | None 
= None) -> dict[str, Any]:
+        vpc_endpoint_id = self._get_graph_endpoint_id()
+        if event:
+            status = event["status"]
+            if status.lower() != "success":
+                raise NeptunePrivateEndpointCreationFailedError("Endpoint 
failed to create")
+
+        return {"vpc_endpoint_id": vpc_endpoint_id, "graph_id": 
self.graph_identifier, "vpc_id": self.vpc_id}
+
+
+class 
NeptuneDeletePrivateGraphEndpointOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Deletes a Neptune Graph private endpoint.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneDeletePrivateGraphEndpointOperator`
+
+    :param graph_identifier: Neptune Graph id
+    :param vpc_id: VPC where endpoint resides
+    :param wait_for_completion: Whether to wait for the endpoint to be 
deleted. (default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
endpoint to be deleted.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields("graph_identifier", 
"vpc_id")
+
+    def __init__(
+        self,
+        graph_identifier: str,
+        vpc_id: str,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_identifier = graph_identifier
+        self.vpc_id = vpc_id
+        self.wait_for_completion = wait_for_completion
+        self.deferrable = deferrable
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+
+    def execute(self, context: Context) -> None:
+        self.log.info("Deleting private endpoint for graph %s", 
self.graph_identifier)
+
+        result = self.hook.conn.delete_private_graph_endpoint(
+            graphIdentifier=self.graph_identifier, vpcId=self.vpc_id
+        )
+
+        status = result.get("status")
+        endpoint_id = result.get("vpcEndpointId")
+
+        if status == "FAILED":
+            raise NeptunePrivateEndpointDeletionFailedError(
+                f"Failed to delete private endpoint {endpoint_id}"
+            )
+
+        if self.deferrable:
+            self.log.info("Deferring until endpoint %s is deleted", 
endpoint_id)
+            self.defer(
+                trigger=NeptuneGraphPrivateEndpointDeletedTrigger(
+                    aws_conn_id=self.aws_conn_id,
+                    graph_id=self.graph_identifier,
+                    vpc_id=self.vpc_id,
+                    endpoint_id=endpoint_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                ),
+                method_name="execute_complete",
+            )
+        if self.wait_for_completion:
+            self.log.info("Waiting until endpoint %s is deleted", endpoint_id)
+            self.hook.get_waiter("private_graph_endpoint_deleted").wait(
+                graphIdentifier=self.graph_identifier,
+                vpcId=self.vpc_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+            self.log.info("Endpoint %s deleted", endpoint_id)
+
+    def execute_complete(self, context: Context, event: dict[str, Any] | None 
= None) -> None:
+        vpc_endpoint_id = ""
+
+        if event and (event.get("status") or "").lower() == "success":
+            vpc_endpoint_id = event.get("endpoint_id", "Unknown")
+
+            self.log.info("Endpoint id %s deleted", vpc_endpoint_id)
+        else:
+            raise NeptunePrivateEndpointDeletionFailedError("Endpoint failed 
to delete.")
+
+
+class NeptuneDeleteGraphOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Deletes an Amazon Neptune Graph database.
+
+    Neptune Analytics is a memory-optimized graph database engine for 
analytics. With Neptune Analytics, you can get insights and find trends by 
processing large amounts of graph data in seconds.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneDeleteGraphOperator`
+
+    :param graph_id: Name of Neptune graph to delete
+    :param skip_snapshot: Determines whether a final graph snapshot is created 
before the graph is deleted. If true is specified, no graph snapshot is 
created. If false is specified, a graph snapshot is created before the graph is 
deleted.
+    :param wait_for_completion: Whether to wait for the graph to delete. 
(default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
graph to be deleted.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields("graph_id", 
"skip_snapshot")
+
+    def __init__(
+        self,
+        graph_id: str,
+        skip_snapshot: bool,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_id = graph_id
+        self.skip_snapshot = skip_snapshot
+        self.wait_for_completion = wait_for_completion
+        self.deferrable = deferrable
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+
+    def execute(self, context: Context):
+        self.log.info("Deleting graph %s", self.graph_id)
+
+        try:
+            self.hook.conn.delete_graph(graphIdentifier=self.graph_id, 
skipSnapshot=self.skip_snapshot)
+        except ClientError as e:
+            # if not found, just exit because there is nothing to delete
+            if e.response["Error"]["Code"] == "ResourceNotFoundException":
+                self.log.info("Graph %s not found. Nothing to delete", 
self.graph_id)
+                return
+            raise NeptuneGraphDeletionFailedError(e.response["Error"])
+
+        if self.deferrable:
+            self.log.info("Deferring until graph %s is deleted", self.graph_id)
+            self.defer(
+                trigger=NeptuneGraphDeletedTrigger(
+                    aws_conn_id=self.aws_conn_id,
+                    graph_id=self.graph_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                ),
+                method_name="execute_complete",
+            )
+        if self.wait_for_completion:
+            self.log.info("Waiting to delete %s", self.graph_id)
+
+            self.hook.get_waiter("graph_deleted").wait(
+                graphIdentifier=self.graph_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+
+    def execute_complete(self, context: Context, event: dict[str, Any] | None 
= None):
+        if event:
+            graph_id = event.get("graph_id", "Unknown")

Review Comment:
   The base trigger returns an event with status error. 
   
   event["status"] is never read. If the trigger emits {"status": "error", 
"graph_id": "g-foo", ...}, this method logs "Neptune graph g-foo deleted" and 
returns None. Task = SUCCESS.
   
   
   



##########
providers/amazon/src/airflow/providers/amazon/aws/links/ec2.py:
##########
@@ -44,3 +44,14 @@ class EC2InstanceDashboardLink(BaseAwsLink):
     @staticmethod
     def format_instance_id_filter(instance_ids: list[str]) -> str:
         return ",:".join(instance_ids)
+
+
+class VpcEndpointLink(BaseAwsLink):

Review Comment:
   Wondering if this should be in vpc.py



##########
providers/amazon/tests/system/amazon/aws/example_neptune_analytics.py:
##########
@@ -0,0 +1,335 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from __future__ import annotations
+
+import contextlib
+import json
+import time
+from datetime import datetime
+
+import boto3
+
+from airflow.providers.amazon.aws.hooks.neptune_analytics import 
NeptuneAnalyticsHook
+from airflow.providers.amazon.aws.operators.neptune_analytics import (
+    NeptuneCancelImportTaskOperator,
+    NeptuneCreateGraphOperator,
+    NeptuneCreateGraphWithImportOperator,
+    NeptuneCreatePrivateGraphEndpointOperator,
+    NeptuneDeleteGraphOperator,
+    NeptuneDeletePrivateGraphEndpointOperator,
+    NeptuneStartImportTaskOperator,
+)
+from airflow.providers.amazon.aws.operators.s3 import (
+    S3CreateBucketOperator,
+    S3CreateObjectOperator,
+    S3DeleteBucketOperator,
+)
+from airflow.providers.common.compat.sdk import DAG, chain, task
+
+try:
+    from airflow.sdk import TriggerRule
+except ImportError:
+    # Compatibility for Airflow < 3.1
+    from airflow.utils.trigger_rule import TriggerRule  # type: 
ignore[no-redef,attr-defined]
+
+from system.amazon.aws.utils import SystemTestContextBuilder
+
+DAG_ID = "example_neptune_analytics"
+
+ROLE_ARN_KEY = "ROLE_ARN"
+
+sys_test_context_task = 
SystemTestContextBuilder().add_variable(ROLE_ARN_KEY).build()

Review Comment:
   doesnt look like we are using this as dag is creating it's own role



##########
providers/amazon/src/airflow/providers/amazon/aws/operators/neptune_analytics.py:
##########
@@ -0,0 +1,1006 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from __future__ import annotations
+
+from collections.abc import Sequence
+from typing import TYPE_CHECKING, Any
+
+from botocore.exceptions import ClientError
+
+from airflow.providers.amazon.aws.hooks.neptune_analytics import 
NeptuneAnalyticsHook
+from airflow.providers.amazon.aws.links.ec2 import VpcEndpointLink
+from airflow.providers.amazon.aws.links.neptune_analytics import 
NeptuneGraphLink, NeptuneImportTaskLink
+from airflow.providers.amazon.aws.operators.base_aws import AwsBaseOperator
+from airflow.providers.amazon.aws.triggers.neptune_analytics import (
+    NeptuneGraphAvailableTrigger,
+    NeptuneGraphDeletedTrigger,
+    NeptuneGraphPrivateEndpointAvailableTrigger,
+    NeptuneGraphPrivateEndpointDeletedTrigger,
+    NeptuneImportTaskCancelledTrigger,
+    NeptuneImportTaskCompleteTrigger,
+)
+from airflow.providers.amazon.aws.utils.mixins import aws_template_fields
+from airflow.providers.common.compat.sdk import conf
+
+if TYPE_CHECKING:
+    from airflow.sdk import Context
+
+from airflow.providers.amazon.aws.exceptions import (
+    NeptuneGraphCreationFailedError,
+    NeptuneGraphDeletionFailedError,
+    NeptuneImportTaskCancellationFailedError,
+    NeptunePrivateEndpointCreationFailedError,
+    NeptunePrivateEndpointDeletionFailedError,
+)
+
+
+class NeptuneCreateGraphOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Creates an empty Amazon Neptune Graph database.
+
+    Neptune Analytics is a memory-optimized graph database engine for 
analytics. With Neptune Analytics, you can get insights and find trends by 
processing large amounts of graph data in seconds.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneCreateGraphOperator`
+
+    :param graph_name: Name of Neptune graph to create
+    :param vector_search_config: Specifies the number of dimensions for vector 
embeddings that will be loaded into the graph.
+    :param provisioned_memory: The provisioned memory-optimized Neptune 
Capacity Units (m-NCUs) to use for the graph.
+    :param public_connectivity: Specifies whether or not the graph can be 
reachable over the internet.
+    :param replica_count: The number of replicas in other AZs.
+    :param deletion_protection:  Indicates whether or not to enable deletion 
protection on the graph.
+        The graph can't be deleted when deletion protection is enabled.
+    :param kms_key_id:  Specifies a KMS key to use to encrypt data in the new 
graph.
+    :param tags: Specifies metadata tags to add to the graph.
+    :param wait_for_completion: Whether to wait for the graph to start. 
(default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
graph to start.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields(
+        "graph_name", "vector_search_config", "provisioned_memory"
+    )
+
+    template_fields_renderers = {
+        "vector_search_config": "json",
+    }
+
+    operator_extra_links = (NeptuneGraphLink(),)
+
+    def __init__(
+        self,
+        graph_name: str,
+        vector_search_config: dict,
+        provisioned_memory: int,
+        public_connectivity: bool | None = None,
+        replica_count: int | None = None,
+        deletion_protection: bool = False,
+        kms_key_id: str | None = None,
+        tags: dict | None = None,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_name = graph_name
+        self.vector_search_config = vector_search_config
+        self.replica_count = replica_count
+        self.provisioned_memory = provisioned_memory
+        self.public_connectivity = public_connectivity
+        self.deletion_protect = deletion_protection
+        self.kms_key = kms_key_id

Review Comment:
   Inconsistent names here. we can match the parm names



##########
providers/amazon/src/airflow/providers/amazon/aws/operators/neptune_analytics.py:
##########
@@ -0,0 +1,1006 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from __future__ import annotations
+
+from collections.abc import Sequence
+from typing import TYPE_CHECKING, Any
+
+from botocore.exceptions import ClientError
+
+from airflow.providers.amazon.aws.hooks.neptune_analytics import 
NeptuneAnalyticsHook
+from airflow.providers.amazon.aws.links.ec2 import VpcEndpointLink
+from airflow.providers.amazon.aws.links.neptune_analytics import 
NeptuneGraphLink, NeptuneImportTaskLink
+from airflow.providers.amazon.aws.operators.base_aws import AwsBaseOperator
+from airflow.providers.amazon.aws.triggers.neptune_analytics import (
+    NeptuneGraphAvailableTrigger,
+    NeptuneGraphDeletedTrigger,
+    NeptuneGraphPrivateEndpointAvailableTrigger,
+    NeptuneGraphPrivateEndpointDeletedTrigger,
+    NeptuneImportTaskCancelledTrigger,
+    NeptuneImportTaskCompleteTrigger,
+)
+from airflow.providers.amazon.aws.utils.mixins import aws_template_fields
+from airflow.providers.common.compat.sdk import conf
+
+if TYPE_CHECKING:
+    from airflow.sdk import Context
+
+from airflow.providers.amazon.aws.exceptions import (
+    NeptuneGraphCreationFailedError,
+    NeptuneGraphDeletionFailedError,
+    NeptuneImportTaskCancellationFailedError,
+    NeptunePrivateEndpointCreationFailedError,
+    NeptunePrivateEndpointDeletionFailedError,
+)
+
+
+class NeptuneCreateGraphOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Creates an empty Amazon Neptune Graph database.
+
+    Neptune Analytics is a memory-optimized graph database engine for 
analytics. With Neptune Analytics, you can get insights and find trends by 
processing large amounts of graph data in seconds.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneCreateGraphOperator`
+
+    :param graph_name: Name of Neptune graph to create
+    :param vector_search_config: Specifies the number of dimensions for vector 
embeddings that will be loaded into the graph.
+    :param provisioned_memory: The provisioned memory-optimized Neptune 
Capacity Units (m-NCUs) to use for the graph.
+    :param public_connectivity: Specifies whether or not the graph can be 
reachable over the internet.
+    :param replica_count: The number of replicas in other AZs.
+    :param deletion_protection:  Indicates whether or not to enable deletion 
protection on the graph.
+        The graph can't be deleted when deletion protection is enabled.
+    :param kms_key_id:  Specifies a KMS key to use to encrypt data in the new 
graph.
+    :param tags: Specifies metadata tags to add to the graph.
+    :param wait_for_completion: Whether to wait for the graph to start. 
(default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
graph to start.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields(
+        "graph_name", "vector_search_config", "provisioned_memory"
+    )
+
+    template_fields_renderers = {
+        "vector_search_config": "json",
+    }
+
+    operator_extra_links = (NeptuneGraphLink(),)
+
+    def __init__(
+        self,
+        graph_name: str,
+        vector_search_config: dict,
+        provisioned_memory: int,
+        public_connectivity: bool | None = None,
+        replica_count: int | None = None,
+        deletion_protection: bool = False,
+        kms_key_id: str | None = None,
+        tags: dict | None = None,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_name = graph_name
+        self.vector_search_config = vector_search_config
+        self.replica_count = replica_count
+        self.provisioned_memory = provisioned_memory
+        self.public_connectivity = public_connectivity
+        self.deletion_protect = deletion_protection
+        self.kms_key = kms_key_id
+        self.tags = tags
+        self.wait_for_completion = wait_for_completion
+        self.deferrable = deferrable
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+
+    def execute(self, context: Context) -> dict:
+        self.log.info("Creating graph %s", self.graph_name)
+
+        create_params = {
+            "graphName": self.graph_name,
+            "vectorSearchConfiguration": self.vector_search_config,
+            "provisionedMemory": self.provisioned_memory,
+            **{
+                k: v
+                for k, v in {
+                    "replicaCount": self.replica_count,
+                    "publicConnectivity": self.public_connectivity,
+                    "deletionProtection": self.deletion_protect,
+                    "kmsKeyIdentifier": self.kms_key,
+                    "tags": self.tags,
+                }.items()
+                if v is not None
+            },
+        }
+
+        response = self.hook.conn.create_graph(**create_params)
+
+        self.log.info("Graph %s in status %s", self.graph_name, 
response.get("status", "Unknown"))
+        self.graph_id = response.get("id", None)
+
+        graph_url = NeptuneGraphLink.format_str.format(
+            graph_id=self.graph_id,
+            
aws_domain=NeptuneGraphLink.get_aws_domain(self.hook.conn_partition),
+            region_name=self.hook.conn_region_name,
+        )
+
+        NeptuneGraphLink.persist(
+            context=context,
+            operator=self,
+            region_name=self.hook.conn_region_name,
+            aws_partition=self.hook.conn_partition,
+            graph_id=self.graph_id,
+        )
+        self.log.info("You can view this Neptune Graph at : %s", graph_url)
+
+        if self.deferrable:
+            self.log.info("Deferring until graph %s is available", 
self.graph_id)
+            self.defer(
+                trigger=NeptuneGraphAvailableTrigger(
+                    aws_conn_id=self.aws_conn_id,
+                    graph_id=self.graph_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                ),
+                method_name="execute_complete",
+            )
+
+        if self.wait_for_completion:
+            self.log.info("Waiting until graph %s is available", self.graph_id)
+            self.hook.get_waiter("graph_available").wait(
+                graphIdentifier=self.graph_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+
+        return {"graph_id": self.graph_id}
+
+    def execute_complete(self, context: Context, event: dict[str, Any] | None 
= None) -> dict[str, Any]:
+        if event is None:
+            raise NeptuneGraphCreationFailedError(
+                "No event received while waiting for Neptune graph creation to 
complete."
+            )
+
+        if event.get("status") != "success":
+            raise NeptuneGraphCreationFailedError(
+                event.get(
+                    "message",
+                    f"Neptune graph {self.graph_id} creation did not complete 
successfully: {event}",
+                )
+            )
+
+        self.log.info("Neptune graph %s complete", self.graph_id)
+
+        return {"graph_id": self.graph_id}
+
+
+class 
NeptuneCreatePrivateGraphEndpointOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Creates a Neptune Graph private endpoint.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneCreatePrivateGraphEndpointOperator`
+
+    :param graph_identifier: Neptune Graph id
+    :param vpc_id: VPC to create endpoint in
+    :param subnet_ids: Subnets in which private graph endpoint ENIs are created
+    :param vpc_security_group_ids: Security groups to be attached to the 
private graph endpoint
+    :param wait_for_completion: Whether to wait for the endpoint to be 
available. (default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
endpoint to become available.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields(
+        "graph_identifier", "vpc_id", "subnet_ids", "vpc_security_group_ids"
+    )
+
+    def __init__(
+        self,
+        graph_identifier: str,
+        vpc_id: str | None = None,
+        subnet_ids: list[str] | None = None,
+        vpc_security_group_ids: list[str] | None = None,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_identifier = graph_identifier
+        self.vpc_id = vpc_id
+        self.subnet_ids = subnet_ids
+        self.vpc_security_group_ids = vpc_security_group_ids
+        self.wait_for_completion = wait_for_completion
+        self.deferrable = deferrable
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+
+    def execute(self, context: Context) -> dict:
+        self.log.info("Creating private endpoint for graph %s", 
self.graph_identifier)
+
+        create_params = {
+            "graphIdentifier": self.graph_identifier,
+            **{
+                k: v
+                for k, v in {
+                    "vpcId": self.vpc_id,
+                    "subnetIds": self.subnet_ids,
+                    "vpcSecurityGroupIds": self.vpc_security_group_ids,
+                }.items()
+                if v is not None
+            },
+        }
+
+        # create the endpoint
+
+        result = self.hook.conn.create_private_graph_endpoint(**create_params)
+        status = result.get("status", "Unknown")
+
+        self.log.info("Status of endpoint: %s", status)
+
+        if status in ["FAILED"]:
+            raise NeptunePrivateEndpointCreationFailedError(
+                f"Private endpoint failed to create for graph 
{self.graph_identifier}"
+            )
+
+        # if VPC not provided, use the one that is returned, which is the 
default VPC. Required for the waiter
+        self.vpc_id = result.get("vpcId", self.vpc_id)
+
+        if self.deferrable:
+            self.log.info("Deferring until endpoint is available")
+            self.defer(
+                trigger=NeptuneGraphPrivateEndpointAvailableTrigger(
+                    aws_conn_id=self.aws_conn_id,
+                    graph_id=self.graph_identifier,
+                    vpc_id=self.vpc_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                ),
+                method_name="execute_complete",
+            )
+
+        if self.wait_for_completion:
+            self.log.info("Waiting until endpoint is available")
+            self.hook.get_waiter("private_graph_endpoint_available").wait(
+                graphIdentifier=self.graph_identifier,
+                vpcId=self.vpc_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+
+        endpoint_id = self._get_graph_endpoint_id()
+
+        endpoint_url = VpcEndpointLink.format_str.format(
+            endpoint_id=endpoint_id,
+            
aws_domain=VpcEndpointLink.get_aws_domain(self.hook.conn_partition),
+            region_name=self.hook.conn_region_name,
+        )
+
+        VpcEndpointLink.persist(
+            context=context,
+            operator=self,
+            region_name=self.hook.conn_region_name,
+            aws_partition=self.hook.conn_partition,
+            endpoint_id=endpoint_id,
+        )
+        self.log.info("You can view this private endpoint at : %s", 
endpoint_url)
+
+        return {"vpc_endpoint_id": endpoint_id, "graph_id": 
self.graph_identifier, "vpc_id": self.vpc_id}
+
+    def _get_graph_endpoint_id(self):
+        """Return the vpc endpoint id for this graph."""
+        result = self.hook.conn.get_private_graph_endpoint(
+            graphIdentifier=self.graph_identifier, vpcId=self.vpc_id
+        )
+        return result.get("vpcEndpointId")
+
+    def execute_complete(self, context: Context, event: dict[str, Any] | None 
= None) -> dict[str, Any]:
+        vpc_endpoint_id = self._get_graph_endpoint_id()
+        if event:
+            status = event["status"]
+            if status.lower() != "success":
+                raise NeptunePrivateEndpointCreationFailedError("Endpoint 
failed to create")
+
+        return {"vpc_endpoint_id": vpc_endpoint_id, "graph_id": 
self.graph_identifier, "vpc_id": self.vpc_id}
+
+
+class 
NeptuneDeletePrivateGraphEndpointOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Deletes a Neptune Graph private endpoint.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneDeletePrivateGraphEndpointOperator`
+
+    :param graph_identifier: Neptune Graph id
+    :param vpc_id: VPC where endpoint resides
+    :param wait_for_completion: Whether to wait for the endpoint to be 
deleted. (default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
endpoint to be deleted.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields("graph_identifier", 
"vpc_id")
+
+    def __init__(
+        self,
+        graph_identifier: str,
+        vpc_id: str,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_identifier = graph_identifier
+        self.vpc_id = vpc_id
+        self.wait_for_completion = wait_for_completion
+        self.deferrable = deferrable
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+
+    def execute(self, context: Context) -> None:
+        self.log.info("Deleting private endpoint for graph %s", 
self.graph_identifier)
+
+        result = self.hook.conn.delete_private_graph_endpoint(
+            graphIdentifier=self.graph_identifier, vpcId=self.vpc_id
+        )
+
+        status = result.get("status")
+        endpoint_id = result.get("vpcEndpointId")
+
+        if status == "FAILED":
+            raise NeptunePrivateEndpointDeletionFailedError(
+                f"Failed to delete private endpoint {endpoint_id}"
+            )
+
+        if self.deferrable:
+            self.log.info("Deferring until endpoint %s is deleted", 
endpoint_id)
+            self.defer(
+                trigger=NeptuneGraphPrivateEndpointDeletedTrigger(
+                    aws_conn_id=self.aws_conn_id,
+                    graph_id=self.graph_identifier,
+                    vpc_id=self.vpc_id,
+                    endpoint_id=endpoint_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                ),
+                method_name="execute_complete",
+            )
+        if self.wait_for_completion:
+            self.log.info("Waiting until endpoint %s is deleted", endpoint_id)
+            self.hook.get_waiter("private_graph_endpoint_deleted").wait(
+                graphIdentifier=self.graph_identifier,
+                vpcId=self.vpc_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+            self.log.info("Endpoint %s deleted", endpoint_id)
+
+    def execute_complete(self, context: Context, event: dict[str, Any] | None 
= None) -> None:
+        vpc_endpoint_id = ""
+
+        if event and (event.get("status") or "").lower() == "success":
+            vpc_endpoint_id = event.get("endpoint_id", "Unknown")
+
+            self.log.info("Endpoint id %s deleted", vpc_endpoint_id)
+        else:
+            raise NeptunePrivateEndpointDeletionFailedError("Endpoint failed 
to delete.")
+
+
+class NeptuneDeleteGraphOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Deletes an Amazon Neptune Graph database.
+
+    Neptune Analytics is a memory-optimized graph database engine for 
analytics. With Neptune Analytics, you can get insights and find trends by 
processing large amounts of graph data in seconds.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneDeleteGraphOperator`
+
+    :param graph_id: Name of Neptune graph to delete
+    :param skip_snapshot: Determines whether a final graph snapshot is created 
before the graph is deleted. If true is specified, no graph snapshot is 
created. If false is specified, a graph snapshot is created before the graph is 
deleted.
+    :param wait_for_completion: Whether to wait for the graph to delete. 
(default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
graph to be deleted.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields("graph_id", 
"skip_snapshot")
+
+    def __init__(
+        self,
+        graph_id: str,
+        skip_snapshot: bool,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_id = graph_id
+        self.skip_snapshot = skip_snapshot
+        self.wait_for_completion = wait_for_completion
+        self.deferrable = deferrable
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+
+    def execute(self, context: Context):
+        self.log.info("Deleting graph %s", self.graph_id)
+
+        try:
+            self.hook.conn.delete_graph(graphIdentifier=self.graph_id, 
skipSnapshot=self.skip_snapshot)
+        except ClientError as e:
+            # if not found, just exit because there is nothing to delete
+            if e.response["Error"]["Code"] == "ResourceNotFoundException":
+                self.log.info("Graph %s not found. Nothing to delete", 
self.graph_id)
+                return
+            raise NeptuneGraphDeletionFailedError(e.response["Error"])
+
+        if self.deferrable:
+            self.log.info("Deferring until graph %s is deleted", self.graph_id)
+            self.defer(
+                trigger=NeptuneGraphDeletedTrigger(
+                    aws_conn_id=self.aws_conn_id,
+                    graph_id=self.graph_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                ),
+                method_name="execute_complete",
+            )
+        if self.wait_for_completion:
+            self.log.info("Waiting to delete %s", self.graph_id)
+
+            self.hook.get_waiter("graph_deleted").wait(
+                graphIdentifier=self.graph_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+
+    def execute_complete(self, context: Context, event: dict[str, Any] | None 
= None):
+        if event:
+            graph_id = event.get("graph_id", "Unknown")
+
+            self.log.info("Neptune graph %s deleted", graph_id)
+
+
+class 
NeptuneCreateGraphWithImportOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Creates a Neptune Graph and imports data into it.
+
+    Neptune Analytics is a memory-optimized graph database engine for 
analytics. With Neptune Analytics,
+    you can get insights and find trends by processing large amounts of graph 
data in seconds.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneCreateGraphWithImportOperator`
+
+    :param graph_name: Name of Neptune graph to create
+    :param vector_search_config: Specifies the number of dimensions for vector 
embeddings that will be loaded into the graph.
+    :param source: The source from which to import data. Can be an S3 URI or 
Neptune database snapshot.
+    :param role_arn: The ARN of the IAM role that Neptune Analytics can assume 
to access the data source.
+    :param blank_node_handling: The method to handle blank nodes in the 
dataset. Options include 'convertToIri' or other handling strategies.
+    :param parquet_type: The type of Parquet files in the data source (if 
applicable).
+    :param format: The format of the data to be imported (e.g., 'csv', 
'opencypher', 'ntriples', 'nquads', 'rdfxml', 'turtle').
+    :param min_provisioned_memory: The minimum provisioned memory for the 
graph in GBs.
+    :param max_provisioned_memory: The maximum provisioned memory for the 
graph in GBs.
+    :param fail_on_error: If True, the import will fail if any errors are 
encountered. If False, the import will continue despite errors.
+    :param public_connectivity: Specifies whether or not the graph can be 
reachable over the internet.
+    :param replica_count: The number of replicas in other AZs.
+    :param deletion_protection: Indicates whether or not to enable deletion 
protection on the graph.
+        The graph can't be deleted when deletion protection is enabled. 
(default: False)
+    :param kms_key_id: Specifies a KMS key to use to encrypt data in the new 
graph.
+    :param tags: Specifies metadata tags to add to the graph.
+    :param import_options: Contains options for controlling the import process.
+    :param wait_for_completion: Whether to wait for the graph to be created 
and data imported. (default: True)
+    :param waiter_delay: Time in seconds to wait between status checks. 
(default: 30)
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion. (default: 60)
+    :param deferrable: If True, the operator will wait asynchronously for the 
graph to be created and data imported.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields(
+        "graph_name", "vector_search_config", "source", "role_arn", "kms_key"
+    )
+
+    template_fields_renderers = {
+        "vector_search_config": "json",
+    }
+
+    operator_extra_links = (
+        NeptuneImportTaskLink(),
+        NeptuneGraphLink(),
+    )
+
+    def __init__(
+        self,
+        graph_name: str,
+        vector_search_config: dict,
+        source: str,
+        role_arn: str,
+        blank_node_handling: str | None = None,
+        parquet_type: str | None = None,
+        format: str | None = None,
+        min_provisioned_memory: int | None = None,
+        max_provisioned_memory: int | None = None,
+        fail_on_error: bool | None = None,
+        public_connectivity: bool | None = None,
+        replica_count: int | None = None,
+        deletion_protection: bool | None = None,
+        kms_key_id: str | None = None,
+        tags: dict | None = None,
+        import_options: dict | None = None,
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_name = graph_name
+        self.vector_search_config = vector_search_config
+        self.source = source
+        self.role_arn = role_arn
+        self.blank_node_handling = blank_node_handling
+        self.parquet_type = parquet_type
+        self.format = format
+        self.min_provisioned_memory = min_provisioned_memory
+        self.max_provisioned_memory = max_provisioned_memory
+        self.fail_on_error = fail_on_error
+        self.public_connectivity = public_connectivity
+        self.replica_count = replica_count
+        self.deletion_protect = deletion_protection
+        self.kms_key = kms_key_id
+        self.tags = tags
+        self.import_options = import_options
+        self.wait_for_completion = wait_for_completion
+        self.deferrable = deferrable
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+
+    def execute(self, context: Context) -> dict:
+        self.log.info("Creating graph %s with import", self.graph_name)
+
+        # Build the import options
+        import_options = {
+            "neptune-analytics:blank-node-handling": self.blank_node_handling,
+            "neptune-analytics:parquet-type": self.parquet_type,
+        }
+
+        # Remove None values from import_options
+        import_options = {k: v for k, v in import_options.items() if v is not 
None}
+
+        # Merge with user-provided import_options
+        if self.import_options:
+            import_options.update(self.import_options)
+
+        create_params = {
+            "graphName": self.graph_name,
+            "vectorSearchConfiguration": self.vector_search_config,
+            "source": self.source,
+            "roleArn": self.role_arn,
+            **{
+                k: v
+                for k, v in {
+                    "format": self.format,
+                    "minProvisionedMemory": self.min_provisioned_memory,
+                    "maxProvisionedMemory": self.max_provisioned_memory,
+                    "failOnError": self.fail_on_error,
+                    "replicaCount": self.replica_count,
+                    "publicConnectivity": self.public_connectivity,
+                    "deletionProtection": self.deletion_protect,
+                    "kmsKeyIdentifier": self.kms_key,
+                    "tags": self.tags,
+                    "importOptions": import_options if import_options else 
None,
+                }.items()
+                if v is not None
+            },
+        }
+
+        response = 
self.hook.conn.create_graph_using_import_task(**create_params)
+
+        self.log.info("Graph %s import task in status %s", self.graph_name, 
response.get("status", "Unknown"))
+        self.graph_id = response.get("graphId", None)
+        import_task_id = response.get("taskId")
+
+        graph_url = NeptuneGraphLink.format_str.format(
+            graph_id=self.graph_id,
+            
aws_domain=NeptuneGraphLink.get_aws_domain(self.hook.conn_partition),
+            region_name=self.hook.conn_region_name,
+        )
+
+        NeptuneGraphLink.persist(
+            context=context,
+            operator=self,
+            region_name=self.hook.conn_region_name,
+            aws_partition=self.hook.conn_partition,
+            graph_id=self.graph_id,
+        )
+
+        import_task_url = NeptuneImportTaskLink.format_str.format(
+            import_task_id=import_task_id,
+            
aws_domain=NeptuneImportTaskLink.get_aws_domain(self.hook.conn_partition),
+            region_name=self.hook.conn_region_name,
+        )
+
+        NeptuneImportTaskLink.persist(
+            context=context,
+            operator=self,
+            region_name=self.hook.conn_region_name,
+            aws_partition=self.hook.conn_partition,
+            import_task_id=import_task_id,
+        )
+
+        self.log.info("You can view this import task at : %s", import_task_url)
+
+        self.log.info("You can view this Neptune Graph at : %s", graph_url)
+
+        if self.deferrable:
+            self.log.info("Deferring until graph %s is available", 
self.graph_id)
+            self.defer(
+                trigger=NeptuneGraphAvailableTrigger(
+                    aws_conn_id=self.aws_conn_id,
+                    graph_id=self.graph_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                ),
+                method_name="defer_wait_for_task",
+                kwargs={"import_task_id": import_task_id},
+            )
+
+        if self.wait_for_completion:
+            self.log.info("Waiting until graph %s is available", self.graph_id)
+            self.hook.get_waiter("graph_available").wait(
+                graphIdentifier=self.graph_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+            # Once the graph is available, wait for the task to complete
+
+            self.log.info("Waiting for import task %s", import_task_id)
+            self.hook.get_waiter("import_task_successful").wait(
+                taskIdentifier=import_task_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+
+        return {"graph_id": self.graph_id}
+
+    def defer_wait_for_task(
+        self, context: Context, event: dict[str, Any] | None = None, 
import_task_id: str | None = None
+    ) -> None:
+        """Defers for import task completion."""
+        if import_task_id:
+            self.log.info("Deferring for import task %s completion", 
import_task_id)
+            self.defer(
+                trigger=NeptuneImportTaskCompleteTrigger(
+                    import_task_id=import_task_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                    aws_conn_id=self.aws_conn_id,
+                ),
+                method_name="execute_complete",
+            )
+
+    def execute_complete(self, context: Context, event: dict[str, Any] | None 
= None) -> dict[str, Any]:
+        if event is None or event.get("status") != "success":
+            message = (event or {}).get(
+                "message", f"Neptune graph {self.graph_id} import did not 
complete successfully"
+            )
+            raise NeptuneGraphCreationFailedError(message)
+        self.log.info("Import complete for graph %s", self.graph_id)
+        return {"graph_id": self.graph_id}
+
+
+class NeptuneStartImportTaskOperator(AwsBaseOperator[NeptuneAnalyticsHook]):
+    """
+    Starts a bulk data import task to load data into an empty Neptune graph.
+
+    .. seealso::
+        For more information on how to use this operator, take a look at the 
guide:
+        :ref:`howto/operator:NeptuneStartImportTaskOperator`
+
+    :param graph_identifier: Graph Id of target Neptune Graph
+    :param role_arn: IAM role ARN granting access to source data
+    :param source: URL identifying the source data location.
+    :param blank_node_handling: Method to handle blank nodes in dataset.
+    :param fail_on_error: If set to true, the task halts when an import error 
is encountered. If set to false, the task skips the data that caused the error 
and continues if possible.
+    :param format: Specifies the format of the Amazon S3 data to be imported.
+    :param import_options: Options on how to perform an import
+    :param parquet_type: Parquet type of import task
+    :param wait_for_completion: Whether to wait for the endpoint to be 
available. (default: True)
+    :param deferrable: If True, the operator will wait asynchronously for the 
endpoint to become available.
+        This implies waiting for completion. This mode requires aiobotocore 
module to be installed.
+        (default: False)
+    :param waiter_delay: Time in seconds to wait between status checks.
+    :param waiter_max_attempts: Maximum number of attempts to check for job 
completion.
+    :param aws_conn_id: The Airflow connection used for AWS credentials.
+        If this is ``None`` or empty then the default boto3 behaviour is used. 
If
+        running Airflow in a distributed manner and aws_conn_id is None or
+        empty, then default boto3 configuration would be used (and must be
+        maintained on each worker node).
+    :param region_name: AWS region_name. If not specified then the default 
boto3 behaviour is used.
+    :param botocore_config: Configuration dictionary (key-values) for botocore 
client. See:
+        
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
+    :return: dictionary with Neptune graph id
+    """
+
+    aws_hook_class = NeptuneAnalyticsHook
+    template_fields: Sequence[str] = aws_template_fields(
+        "graph_identifier", "role_arn", "source", "import_options"
+    )
+    template_fields_renderers = {
+        "import_options": "json",
+    }
+    operator_extra_links = (NeptuneImportTaskLink(),)
+
+    def __init__(
+        self,
+        graph_identifier: str,
+        role_arn: str,
+        source: str,
+        blank_node_handling: str | None = None,
+        fail_on_error: bool = True,
+        format: str | None = None,
+        import_options: dict | None = None,
+        parquet_type: str | None = "COLUMNAR",
+        wait_for_completion: bool = True,
+        waiter_delay: int = 30,
+        waiter_max_attempts: int = 60,
+        deferrable: bool = conf.getboolean("operators", "default_deferrable", 
fallback=False),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.graph_identifier = graph_identifier
+        self.role_arn = role_arn
+        self.source = source
+        self.blank_node_handling = blank_node_handling
+        self.fail_on_error = fail_on_error
+        self.format = format
+        self.import_options = import_options
+        self.parquet_type = parquet_type
+        self.wait_for_completion = wait_for_completion
+        self.waiter_delay = waiter_delay
+        self.waiter_max_attempts = waiter_max_attempts
+        self.deferrable = deferrable
+
+    def execute(self, context: Context) -> dict:
+        self.log.info("Starting data import to graph %s", 
self.graph_identifier)
+
+        create_params = {
+            "graphIdentifier": self.graph_identifier,
+            "roleArn": self.role_arn,
+            "source": self.source,
+            **{
+                k: v
+                for k, v in {
+                    "blankNodeHandling": self.blank_node_handling,
+                    "failOnError": self.fail_on_error,
+                    "format": self.format,
+                    "importOptions": self.import_options,
+                    "parquetType": self.parquet_type,
+                }.items()
+                if v is not None
+            },
+        }
+
+        response = self.hook.conn.start_import_task(**create_params)
+        import_task_id = response.get("taskId")
+        self.log.info("Import task %s started for graph %s", import_task_id, 
self.graph_identifier)
+
+        # Create the console link
+        import_task_url = NeptuneImportTaskLink.format_str.format(
+            import_task_id=import_task_id,
+            
aws_domain=NeptuneImportTaskLink.get_aws_domain(self.hook.conn_partition),
+            region_name=self.hook.conn_region_name,
+        )
+
+        NeptuneImportTaskLink.persist(
+            context=context,
+            operator=self,
+            region_name=self.hook.conn_region_name,
+            aws_partition=self.hook.conn_partition,
+            import_task_id=import_task_id,
+        )
+        self.log.info("You can view this import task at : %s", import_task_url)
+
+        if self.deferrable:
+            self.log.info("Deferring until import task %s completes", 
import_task_id)
+            self.defer(
+                trigger=NeptuneImportTaskCompleteTrigger(
+                    import_task_id=import_task_id,
+                    waiter_delay=self.waiter_delay,
+                    waiter_max_attempts=self.waiter_max_attempts,
+                    aws_conn_id=self.aws_conn_id,
+                ),
+                method_name="execute_complete",
+            )
+
+        if self.wait_for_completion:
+            self.log.info("Waiting for import task %s to complete", 
import_task_id)
+            self.hook.get_waiter("import_task_successful").wait(
+                taskIdentifier=import_task_id,
+                WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": 
self.waiter_max_attempts},
+            )
+
+        return {"import_task_id": import_task_id, "graph_id": 
self.graph_identifier}
+
+    def execute_complete(self, context: Context, event: dict[str, Any] | None 
= None) -> dict[str, Any]:
+        task_id = ""
+        if event:
+            task_id = event.get("import_task_id", "")

Review Comment:
   same issue. I think we need to check if the trigger event has returned 
success or error.\
   NeptuneCreateGraphOperator.execute_complete (line 190) and 
NeptuneCancelImportTaskOperator.execute_complete (line 991) already do the 
check correctly — please apply the same pattern, ideally via 



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