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commit a4ecfe862263fa70f166c0dafae835faa840f761 Author: Kyle Weller <[email protected]> AuthorDate: Wed Feb 28 21:36:18 2024 -0800 homepage and docs updated --- website/README.md | 6 +- website/docs/athena.md | 6 +- website/docs/biglake-metastore.md | 20 ++-- website/docs/bigquery.md | 10 +- website/docs/catalogs-index.md | 2 +- website/docs/demo/docker.md | 10 +- website/docs/fabric.md | 10 +- website/docs/features-and-limitations.md | 4 +- website/docs/glue-catalog.md | 8 +- website/docs/hms.md | 18 +-- website/docs/how-to.md | 16 +-- website/docs/integrations-index.md | 2 +- website/docs/presto.md | 14 +-- website/docs/query-engines-index.md | 4 +- website/docs/redshift.md | 4 +- website/docs/setup.md | 6 +- website/docs/snowflake.md | 2 +- website/docs/spark.md | 2 +- website/docs/starrocks.md | 10 +- website/docs/trino.md | 10 +- website/docs/unity-catalog.md | 10 +- website/docusaurus.config.js | 8 +- website/static/css/onetable-ad267e.webflow.css | 25 +++- website/static/images/apache-incubator.svg | 1 + website/static/images/destination-1.png | Bin 20714 -> 19506 bytes website/static/images/source-2.png | Bin 20828 -> 19568 bytes website/static/images/write-query.png | Bin 0 -> 189407 bytes website/static/images/xtable-hero.svg | 147 ++++++++++++++++++++++++ website/static/images/xtable-icon-white-svg.svg | 58 ++++++++++ website/static/images/xtable-icon-white.png | Bin 0 -> 83504 bytes website/static/images/xtable-icon.png | Bin 0 -> 115580 bytes website/static/images/xtable-svg.svg | 70 +++++++++++ website/static/images/xtable-white-svg.svg | 70 +++++++++++ website/static/images/xtable-white.png | Bin 0 -> 60873 bytes website/static/images/xtable-words-white.png | Bin 0 -> 15321 bytes website/static/images/xtable-words.png | Bin 0 -> 16972 bytes website/static/images/xtable.png | Bin 0 -> 77607 bytes website/static/index.html | 95 +++++++-------- 38 files changed, 502 insertions(+), 146 deletions(-) diff --git a/website/README.md b/website/README.md index b3f09725..f1de62a0 100644 --- a/website/README.md +++ b/website/README.md @@ -1,6 +1,6 @@ -# OneTable Website Source Code +# XTable Website Source Code -This repo hosts the source code of [OneTable](https://onetable.dev) +This repo hosts the source code of [XTable](https://onetable.dev) ## Prerequisite @@ -63,4 +63,4 @@ npm run serve ## Maintainers -OneTable Community +XTable Community diff --git a/website/docs/athena.md b/website/docs/athena.md index 9a9f5ca4..769cd460 100644 --- a/website/docs/athena.md +++ b/website/docs/athena.md @@ -4,7 +4,7 @@ title: "Amazon Athena" --- # Querying from Amazon Athena -To read a OneTable synced target table (regardless of the table format) in Amazon Athena, +To read a XTable synced target table (regardless of the table format) in Amazon Athena, you can create the table either by: * Using a DDL statement as mentioned in the following AWS docs: * [Example](https://docs.aws.amazon.com/athena/latest/ug/querying-hudi.html#querying-hudi-in-athena-creating-hudi-tables) for Hudi @@ -12,8 +12,8 @@ you can create the table either by: * [Example](https://docs.aws.amazon.com/athena/latest/ug/querying-iceberg-creating-tables.html#querying-iceberg-creating-tables-query-editor) for Iceberg * Or maintain the tables in Glue Data Catalog -For an end to end tutorial that walks through S3, Glue Data Catalog and Athena to query a OneTable synced table, -you can refer to the OneTable [Glue Data Catalog Guide](/docs/glue-catalog). +For an end to end tutorial that walks through S3, Glue Data Catalog and Athena to query a XTable synced table, +you can refer to the XTable [Glue Data Catalog Guide](/docs/glue-catalog). :::danger LIMITATION for Hudi target format: To validate the Hudi targetFormat table results, you need to ensure that the query engine that you're using diff --git a/website/docs/biglake-metastore.md b/website/docs/biglake-metastore.md index 8eef46c0..2b108451 100644 --- a/website/docs/biglake-metastore.md +++ b/website/docs/biglake-metastore.md @@ -7,33 +7,33 @@ import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; # Syncing to BigLake Metastore -This document walks through the steps to register a OneTable synced Iceberg table in BigLake Metastore on GCP. +This document walks through the steps to register a XTable synced Iceberg table in BigLake Metastore on GCP. ## Pre-requisites 1. Source (Hudi/Delta) table(s) already written to Google Cloud Storage. If you don't have the source table written in GCS, you can follow the steps in [this](/docs/how-to#create-dataset) tutorial to set it up. -2. To ensure that the BigLake API's caller (your service account used by OneTable) has the +2. To ensure that the BigLake API's caller (your service account used by XTable) has the necessary permissions to create a BigLake table, ask your administrator to grant [BigLake Admin](https://cloud.google.com/iam/docs/understanding-roles#biglake.admin) (roles/bigquery.admin) access to the service account. -3. To ensure that the Storage Account API's caller (your service account used by OneTable) has the +3. To ensure that the Storage Account API's caller (your service account used by XTable) has the necessary permissions to write log/metadata files in GCS, ask your administrator to grant [Storage Object User](https://cloud.google.com/storage/docs/access-control/iam-roles) (roles/storage.objectUser) access to the service account. -4. If you're running OneTable outside GCP, you need to provide the machine access to interact with BigLake and GCS. +4. If you're running XTable outside GCP, you need to provide the machine access to interact with BigLake and GCS. To do so, store the permissions key for your service account in your machine using ```shell export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service_account_key.json ``` -5. Clone the OneTable [repository](https://github.com/onetable-io/onetable) and create the +5. Clone the XTable [repository](https://github.com/onetable-io/onetable) and create the `utilities-0.1.0-SNAPSHOT-bundled.jar` by following the steps on the [Installation page](/docs/setup) 6. Download the [BigLake Iceberg JAR](gs://spark-lib/biglake/biglake-catalog-iceberg1.2.0-0.1.0-with-dependencies.jar) locally. - OneTable requires the JAR to be present in the classpath. + XTable requires the JAR to be present in the classpath. ## Steps :::danger Important: Currently BigLake Metastore is only accessible through Google's [BigLake Rest APIs](https://cloud.google.com/bigquery/docs/reference/biglake/rest), and as such -OneTable requires you to setup the below items prior to running sync on your source dataset. +XTable requires you to setup the below items prior to running sync on your source dataset. * BigLake Catalog * BigLake Database ::: @@ -114,7 +114,7 @@ catalogOptions: warehouse: gs://path/to/warehouse ``` -From your terminal under the cloned OneTable directory, run the sync process using the below command. +From your terminal under the cloned XTable directory, run the sync process using the below command. ```shell md title="shell" java -cp utilities/target/utilities-0.1.0-SNAPSHOT-bundled.jar:/path/to/downloaded/biglake-catalog-iceberg1.2.0-0.1.0-with-dependencies.jar io.onetable.utilities.RunSync --datasetConfig my_config.yaml --icebergCatalogConfig catalog.yaml @@ -127,7 +127,7 @@ to interpret the data as an Iceberg table. ::: ### Validating the results -Once the sync succeeds, OneTable would have written the table directly to BigLake Metastore. +Once the sync succeeds, XTable would have written the table directly to BigLake Metastore. We can use `Try this method` option on Google's REST reference docs for [`projects.locations.catalogs.databases.tables.get`](https://cloud.google.com/bigquery/docs/reference/biglake/rest/v1/projects.locations.catalogs.databases.tables/get) method to view the created table. @@ -137,6 +137,6 @@ projects/<yourProjectName>/locations/us-west1/catalogs/onetable/databases/onetab ## Conclusion In this guide we saw how to, -1. sync a source table to create Iceberg metadata with OneTable +1. sync a source table to create Iceberg metadata with XTable 2. catalog the data as an Iceberg table in BigLake Metastore 3. validate the table creation using `projects.locations.catalogs.databases.tables.get` method diff --git a/website/docs/bigquery.md b/website/docs/bigquery.md index 3ed4fcb8..d3f64cc4 100644 --- a/website/docs/bigquery.md +++ b/website/docs/bigquery.md @@ -6,11 +6,11 @@ title: "Google BigQuery" # Querying from Google BigQuery ### Iceberg tables -To read a OneTable synced [Iceberg table from BigQuery](https://cloud.google.com/bigquery/docs/iceberg-tables), +To read a XTable synced [Iceberg table from BigQuery](https://cloud.google.com/bigquery/docs/iceberg-tables), you have two options: #### [Using Iceberg JSON metadata file to create the Iceberg BigLake tables](https://cloud.google.com/bigquery/docs/iceberg-tables#create-using-metadata-file): -OneTable outputs metadata files for Iceberg target format syncs which can be used by BigQuery +XTable outputs metadata files for Iceberg target format syncs which can be used by BigQuery to read the BigLake tables. ```sql md title="sql" @@ -48,9 +48,9 @@ If you are not planning on using Iceberg, then you do not need to add these to y #### [Using BigLake Metastore to create the Iceberg BigLake tables](https://cloud.google.com/bigquery/docs/iceberg-tables#create-using-biglake-metastore): -You can use two options to register OneTable synced Iceberg tables to BigLake Metastore: -* To directly register the OneTable synced Iceberg table to BigLake Metastore, - follow the [OneTable guide to integrate with BigLake Metastore](/docs/biglake-metastore) +You can use two options to register XTable synced Iceberg tables to BigLake Metastore: +* To directly register the XTable synced Iceberg table to BigLake Metastore, + follow the [XTable guide to integrate with BigLake Metastore](/docs/biglake-metastore) * Use [stored procedures for Spark](https://cloud.google.com/bigquery/docs/spark-procedures) on BigQuery to register the table in BigLake Metastore and query the tables from BigQuery. diff --git a/website/docs/catalogs-index.md b/website/docs/catalogs-index.md index c821f133..4a9e212a 100644 --- a/website/docs/catalogs-index.md +++ b/website/docs/catalogs-index.md @@ -1,6 +1,6 @@ # Catalogs -Integrating the OneTable synced target tables to external catalogs requires an explicit registration. This guide will +Integrating the XTable synced target tables to external catalogs requires an explicit registration. This guide will walk you through the required steps. In addition to the information in this guide, we recommend you following official guidelines from the respective diff --git a/website/docs/demo/docker.md b/website/docs/demo/docker.md index 8848ae31..d610a877 100644 --- a/website/docs/demo/docker.md +++ b/website/docs/demo/docker.md @@ -3,22 +3,22 @@ sidebar_position: 1 title: "Docker Demo" --- -# Building interoperable tables using OneTable -This demo walks you through a fictional use case and the steps to add interoperability between table formats using OneTable. +# Building interoperable tables using XTable +This demo walks you through a fictional use case and the steps to add interoperability between table formats using XTable. For this purpose, a self-contained data infrastructure is brought up as Docker containers within your computer. ## Pre-requisites * Install Docker in your local machine -* Clone [OneTable GitHub repository](https://github.com/onetable-io/onetable) +* Clone [XTable GitHub repository](https://github.com/onetable-io/onetable) :::note NOTE: This demo was tested in both x86-64 and AArch64 based macOS operating systems ::: ## Setting up Docker cluster -After cloning the OneTable repository, change directory to `demo` and run the `start_demo.sh` script. -This script builds OneTable jars required for the demo and then spins up docker containers to start a Jupyter notebook +After cloning the XTable repository, change directory to `demo` and run the `start_demo.sh` script. +This script builds XTable jars required for the demo and then spins up docker containers to start a Jupyter notebook with Scala interpreter, Hive Metastore, Presto and Trino. ```shell md title="shell" diff --git a/website/docs/fabric.md b/website/docs/fabric.md index e83a9c24..0d3f671c 100644 --- a/website/docs/fabric.md +++ b/website/docs/fabric.md @@ -8,8 +8,8 @@ import TabItem from '@theme/TabItem'; # Querying from Microsoft Fabric This guide offers a short tutorial on how to query Apache Iceberg and Apache Hudi tables in Microsoft Fabric utilizing -the translation capabilities of OneTable. This tutorial is intended solely for demonstration and to verify the -compatibility of OneTable's output with Fabric. The tutorial leverages the currently[^1] available features in Fabric, like +the translation capabilities of XTable. This tutorial is intended solely for demonstration and to verify the +compatibility of XTable's output with Fabric. The tutorial leverages the currently[^1] available features in Fabric, like `Shortcuts`. @@ -26,7 +26,7 @@ to data in other file systems. ## Tutorial The objective of the following tutorial is to translate an Iceberg or Hudi table in ADLS storage account into Delta Lake -format using OneTable. After translation, this table will be accessible for querying from various Fabric engines, +format using XTable. After translation, this table will be accessible for querying from various Fabric engines, including T-SQL, Spark, and Power BI. ### Pre-requisites @@ -51,8 +51,8 @@ spark.hadoop.fs.azure.account.oauth2.client.id=<client-id> spark.hadoop.fs.azure.account.oauth2.client.secret=<client-secret> ``` -### Step 2. Translate source table to Delta Lake format using OneTable -This step translates the table `people` originally in Iceberg or Hudi format to Delta Lake format using OneTable. +### Step 2. Translate source table to Delta Lake format using XTable +This step translates the table `people` originally in Iceberg or Hudi format to Delta Lake format using XTable. The primary actions for the translation are documented in [Creating your first interoperable table - Running Sync](/docs/how-to#running-sync) tutorial section. However, since the table is in ADLS, you need to update datasets path and hadoop configurations. diff --git a/website/docs/features-and-limitations.md b/website/docs/features-and-limitations.md index 6fd6aeb0..d2290bc4 100644 --- a/website/docs/features-and-limitations.md +++ b/website/docs/features-and-limitations.md @@ -8,9 +8,9 @@ import TabItem from '@theme/TabItem'; # Features and Limitations ## Features -OneTable provides users with the ability to translate metadata from one table format to another. +XTable provides users with the ability to translate metadata from one table format to another. -OneTable provides two sync modes, "incremental" and "full." The incremental mode is more lightweight and has better performance, especially on large tables. If there is anything that prevents the incremental mode from working properly, the tool will fall back to the full sync mode. +XTable provides two sync modes, "incremental" and "full." The incremental mode is more lightweight and has better performance, especially on large tables. If there is anything that prevents the incremental mode from working properly, the tool will fall back to the full sync mode. This sync provides users with the following: 1. Syncing of data files along with their column level statistics and partition metadata diff --git a/website/docs/glue-catalog.md b/website/docs/glue-catalog.md index 159eadf1..4f9a0e3a 100644 --- a/website/docs/glue-catalog.md +++ b/website/docs/glue-catalog.md @@ -7,7 +7,7 @@ import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; # Syncing to Glue Data Catalog -This document walks through the steps to register a OneTable synced table in Glue Data Catalog on AWS. +This document walks through the steps to register a XTable synced table in Glue Data Catalog on AWS. ## Pre-requisites 1. Source table(s) (Hudi/Delta/Iceberg) already written to Amazon S3. @@ -18,12 +18,12 @@ This document walks through the steps to register a OneTable synced table in Glu [AWS docs](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html) and also set up access credentials by following the steps [here](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-quickstart.html) -3. Clone the OneTable [repository](https://github.com/onetable-io/onetable) and create the +3. Clone the XTable [repository](https://github.com/onetable-io/onetable) and create the `utilities-0.1.0-SNAPSHOT-bundled.jar` by following the steps on the [Installation page](/docs/setup) ## Steps ### Running sync -Create `my_config.yaml` in the cloned OneTable directory. +Create `my_config.yaml` in the cloned XTable directory. <Tabs groupId="table-format" @@ -193,6 +193,6 @@ SELECT * FROM onetable_synced_db.<table_name>; ## Conclusion In this guide we saw how to, -1. sync a source table to create metadata for the desired target table formats using OneTable +1. sync a source table to create metadata for the desired target table formats using XTable 2. catalog the data in the target table format in Glue Data Catalog 3. query the target table using Amazon Athena diff --git a/website/docs/hms.md b/website/docs/hms.md index 2c8dad21..e9d26def 100644 --- a/website/docs/hms.md +++ b/website/docs/hms.md @@ -7,7 +7,7 @@ import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; # Syncing to Hive Metastore -This document walks through the steps to register a OneTable synced table on Hive Metastore (HMS). +This document walks through the steps to register a XTable synced table on Hive Metastore (HMS). ## Pre-requisites 1. Source table(s) (Hudi/Delta/Iceberg) already written to your local storage or external storage locations like S3/GCS/ADLS. @@ -16,14 +16,14 @@ This document walks through the steps to register a OneTable synced table on Hiv 2. A compute instance where you can run Apache Spark. This can be your local machine, docker, or a distributed system like Amazon EMR, Google Cloud's Dataproc, Azure HDInsight etc. This is a required step to register the table in HMS using a Spark client. -3. Clone the OneTable [repository](https://github.com/onetable-io/onetable) and create the +3. Clone the XTable [repository](https://github.com/onetable-io/onetable) and create the `utilities-0.1.0-SNAPSHOT-bundled.jar` by following the steps on the [Installation page](/docs/setup) 4. This guide also assumes that you have configured the Hive Metastore locally or on EMR/Dataproc/HDInsight and is already running. ## Steps ### Running sync -Create `my_config.yaml` in the cloned OneTable directory. +Create `my_config.yaml` in the cloned XTable directory. <Tabs groupId="table-format" @@ -86,7 +86,7 @@ datasets: * ADLS - `abfss://<container-name>@<storage-account-name>.dfs.core.windows.net/<path-to-data>` ::: -From your terminal under the cloned OneTable directory, run the sync process using the below command. +From your terminal under the cloned XTable directory, run the sync process using the below command. ```shell md title="shell" java -jar utilities/target/utilities-0.1.0-SNAPSHOT-bundled.jar --datasetConfig my_config.yaml ``` @@ -97,7 +97,7 @@ directory with relevant metadata files that helps query engines to interpret the ::: ### Register the target table in Hive Metastore -Now you need to register the OneTable synced target table in Hive Metastore. +Now you need to register the XTable synced target table in Hive Metastore. <Tabs groupId="table-format" @@ -137,7 +137,7 @@ if you have your source table in S3/GCS/ADLS i.e. Now you will be able to query the created table directly as a Hudi table from the same `spark` session or -using query engines like `Presto` and/or `Trino`. Check out the guides for querying the OneTable synced tables on +using query engines like `Presto` and/or `Trino`. Check out the guides for querying the XTable synced tables on [Presto](/docs/presto) or [Trino](/docs/trino) query engines for more information. ```sql md title="sql" @@ -171,7 +171,7 @@ if you have your source table in S3/GCS/ADLS i.e. ::: Now you will be able to query the created table directly as a Delta table from the same `spark` session or -using query engines like `Presto` and/or `Trino`. Check out the guides for querying the OneTable synced tables on +using query engines like `Presto` and/or `Trino`. Check out the guides for querying the XTable synced tables on [Presto](/docs/presto) or [Trino](/docs/trino) query engines for more information. ```sql md title="sql" @@ -211,7 +211,7 @@ in S3/GCS/ADLS i.e. ::: Now you will be able to query the created table directly as an Iceberg table from the same `spark` session or -using query engines like `Presto` and/or `Trino`. Check out the guides for querying the OneTable synced tables on +using query engines like `Presto` and/or `Trino`. Check out the guides for querying the XTable synced tables on [Presto](/docs/presto) or [Trino](/docs/trino) query engines for more information. ```sql md title="sql" @@ -223,6 +223,6 @@ SELECT * FROM iceberg_db.<table_name>; ## Conclusion In this guide we saw how to, -1. sync a source table to create metadata for the desired target table formats using OneTable +1. sync a source table to create metadata for the desired target table formats using XTable 2. catalog the data in the target table format in Hive Metastore 3. query the target table using Spark diff --git a/website/docs/how-to.md b/website/docs/how-to.md index cb486d55..21795da7 100644 --- a/website/docs/how-to.md +++ b/website/docs/how-to.md @@ -9,13 +9,13 @@ import TabItem from '@theme/TabItem'; # Creating your first interoperable table :::danger Important -Using OneTable to sync your source tables in different target format involves running sync on your +Using XTable to sync your source tables in different target format involves running sync on your current dataset using a bundled jar. You can create this bundled jar by following the instructions -on the [Installation page](/docs/setup). Read through OneTable's +on the [Installation page](/docs/setup). Read through XTable's [GitHub page](https://github.com/onetable-io/onetable#building-the-project-and-running-tests) for more information. ::: -In this tutorial we will look at how to use OneTable to add interoperability between table formats. +In this tutorial we will look at how to use XTable to add interoperability between table formats. For example, you can expose a table ingested with Hudi as an Iceberg and/or Delta Lake table without copying or moving the underlying data files used for that table while maintaining a similar commit history to enable proper point in time queries. @@ -23,7 +23,7 @@ history to enable proper point in time queries. ## Pre-requisites 1. A compute instance where you can run Apache Spark. This can be your local machine, docker, or a distributed service like Amazon EMR, Google Cloud's Dataproc, Azure HDInsight etc -2. Clone the OneTable [repository](https://github.com/onetable-io/onetable) and create the +2. Clone the XTable [repository](https://github.com/onetable-io/onetable) and create the `utilities-0.1.0-SNAPSHOT-bundled.jar` by following the steps on the [Installation page](/docs/setup) 3. Optional: Setup access to write to and/or read from distributed storage services like: * Amazon S3 by following the steps @@ -33,7 +33,7 @@ history to enable proper point in time queries. * Google Cloud Storage by following the steps [here](https://cloud.google.com/iam/docs/keys-create-delete#creating) -For the purpose of this tutorial, we will walk through the steps to using OneTable locally. +For the purpose of this tutorial, we will walk through the steps to using XTable locally. ## Steps @@ -348,7 +348,7 @@ Authentication for GCP requires service account credentials to be exported. i.e. `export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service_account_key.json` ::: -In your terminal under the cloned OneTable directory, run the below command. +In your terminal under the cloned XTable directory, run the below command. ```shell md title="shell" java -jar utilities/target/utilities-0.1.0-SNAPSHOT-bundled.jar --datasetConfig my_config.yaml @@ -359,9 +359,9 @@ At this point, if you check your local path, you will be able to see the necessa commit history, partitions, and column stats that helps query engines to interpret the data in the target table format. ## Conclusion -In this tutorial, we saw how to create a source table and use OneTable to create the metadata files +In this tutorial, we saw how to create a source table and use XTable to create the metadata files that can be used to query the source table in different target table formats. ## Next steps -Go through the [Catalog Integration guides](/docs/catalogs-index) to register the OneTable synced tables +Go through the [Catalog Integration guides](/docs/catalogs-index) to register the XTable synced tables in different data catalogs. diff --git a/website/docs/integrations-index.md b/website/docs/integrations-index.md index bb92a4c3..cc4ddb64 100644 --- a/website/docs/integrations-index.md +++ b/website/docs/integrations-index.md @@ -1,6 +1,6 @@ # Integrations -This guide will serve as a reference to integrate OneTable synced tables to various +This guide will serve as a reference to integrate XTable synced tables to various catalogs and query engines. In addition to the information in this guide, we recommend you following official guidelines diff --git a/website/docs/presto.md b/website/docs/presto.md index 14832654..2fee5352 100644 --- a/website/docs/presto.md +++ b/website/docs/presto.md @@ -9,7 +9,7 @@ import TabItem from '@theme/TabItem'; # Querying from Presto Presto allows you to query table formats like Hudi, Delta and Iceberg using connectors. The same setup will -work for OneTable synced tables as well. +work for XTable synced tables as well. For more information and required configurations refer to: * [Hudi Connector](https://prestodb.io/docs/current/connector/hudi.html) @@ -19,12 +19,12 @@ For more information and required configurations refer to: :::danger Delta Lake: Delta Lake supports [generated columns](https://docs.databricks.com/en/delta/generated-columns.html) which are a special type of column whose values are automatically generated based on a user-specified function -over other columns in the Delta table. During sync, OneTable uses the same logic to generate partition columns wherever required. -Currently, the generated columns from OneTable sync shows `NULL` when queried from Presto CLI. +over other columns in the Delta table. During sync, XTable uses the same logic to generate partition columns wherever required. +Currently, the generated columns from XTable sync shows `NULL` when queried from Presto CLI. ::: For hands on experimentation, please follow [Creating your first interoperable table](/docs/how-to) tutorial -to create OneTable synced tables followed by [Hive Metastore](/docs/hms) tutorial to register the target table +to create XTable synced tables followed by [Hive Metastore](/docs/hms) tutorial to register the target table in Hive Metastore. Once done, follow the below high level steps: 1. If you are working with a self-managed Presto service, from the presto-server directory run `./bin/launcher run` 2. From the directory where you have installed presto-cli: login to presto-cli by running `./presto-cli` @@ -42,7 +42,7 @@ values={[ <TabItem value="hudi"> :::tip Note: -If you are following the example from [Hive Metastore](/docs/hms), you can query the OneTable synced Hudi table +If you are following the example from [Hive Metastore](/docs/hms), you can query the XTable synced Hudi table from Presto using the below query. ```sql md title="sql" SELECT * FROM hudi.hudi_db.<table_name>; @@ -53,7 +53,7 @@ SELECT * FROM hudi.hudi_db.<table_name>; <TabItem value="delta"> :::tip Note: -If you are following the example from [Hive Metastore](/docs/hms), you can query the OneTable synced Delta table +If you are following the example from [Hive Metastore](/docs/hms), you can query the XTable synced Delta table from Presto using the below query. ```sql md title="sql" SELECT * FROM delta.delta_db.<table_name>; @@ -64,7 +64,7 @@ SELECT * FROM delta.delta_db.<table_name>; <TabItem value="iceberg"> :::tip Note: -If you are following the example from [Hive Metastore](/docs/hms), you can query the OneTable synced Iceberg table +If you are following the example from [Hive Metastore](/docs/hms), you can query the XTable synced Iceberg table from Presto using the below query. ```sql md title="sql" SELECT * FROM iceberg.iceberg_db.<table_name>; diff --git a/website/docs/query-engines-index.md b/website/docs/query-engines-index.md index 24977f99..46266259 100644 --- a/website/docs/query-engines-index.md +++ b/website/docs/query-engines-index.md @@ -1,7 +1,7 @@ # Query Engines -OneTable synced tables behave the similarly to native tables which means you do not need any additional configurations -on query engines' side to work with tables synced by OneTable. This guide will delve into the details of working +XTable synced tables behave the similarly to native tables which means you do not need any additional configurations +on query engines' side to work with tables synced by XTable. This guide will delve into the details of working with various query engines. For more information on how to sync a source format table to create necessary log files to be inferred as a different format table, refer to [Creating your first interoperable table guide](/docs/how-to) diff --git a/website/docs/redshift.md b/website/docs/redshift.md index 0aec1070..17d1ec73 100644 --- a/website/docs/redshift.md +++ b/website/docs/redshift.md @@ -4,7 +4,7 @@ title: "Amazon Redshift Spectrum" --- # Querying from Redshift Spectrum -To read a OneTable synced target table (regardless of the table format) in Amazon Redshift, +To read a XTable synced target table (regardless of the table format) in Amazon Redshift, users have to create an external schema and refer to the external data catalog that contains the table. Redshift infers the table's schema and format from the external catalog/database directly. For more information on creating external schemas, refer to @@ -41,7 +41,7 @@ You have two options to create and query Delta tables in Redshift Spectrum: 1. Follow the steps in [this](https://docs.delta.io/latest/redshift-spectrum-integration.html#set-up-a-redshift-spectrum-to-delta-lake-integration-and-query-delta-tables) article to set up a Redshift Spectrum to Delta Lake integration and query Delta tables directly from Amazon S3. -2. While creating the Glue Crawler to crawl the OneTable synced Delta table, choose the `Create Symlink tables` +2. While creating the Glue Crawler to crawl the XTable synced Delta table, choose the `Create Symlink tables` option in `Add data source` pop-up window. This will add `_symlink_format_manifest` folder with manifest files in the table root path. diff --git a/website/docs/setup.md b/website/docs/setup.md index b1e5901b..cd8d86bf 100644 --- a/website/docs/setup.md +++ b/website/docs/setup.md @@ -1,10 +1,10 @@ # Installation -This page covers the essential steps to setup OneTable in your environment. +This page covers the essential steps to setup XTable in your environment. ## Pre-requisites 1. Building the project requires Java 11 and Maven to be setup and configured using PATH or environment variables. -2. Clone the OneTable project GitHub [repository](https://github.com/onetable-io/onetable) in your environment. +2. Clone the XTable project GitHub [repository](https://github.com/onetable-io/onetable) in your environment. ## Steps #### Building the project @@ -22,5 +22,5 @@ mvn clean package -DskipTests For more information on the steps, follow the project's GitHub [README.md](https://github.com/onetable-io/onetable/blob/main/README.md) ## Next Steps -See the [Quickstart](/docs/how-to) guide to learn to use OneTable to add interoperability between +See the [Quickstart](/docs/how-to) guide to learn to use XTable to add interoperability between different table formats. \ No newline at end of file diff --git a/website/docs/snowflake.md b/website/docs/snowflake.md index 6d632fe7..83d87a11 100644 --- a/website/docs/snowflake.md +++ b/website/docs/snowflake.md @@ -14,7 +14,7 @@ Iceberg on Snowflake is currently supported in ::: ## Steps: -These are high level steps to help you integrate OneTable synced Iceberg tables on Snowflake. For more additional information +These are high level steps to help you integrate XTable synced Iceberg tables on Snowflake. For more additional information refer to the [Getting started with Iceberg tables](https://docs.snowflake.com/LIMITEDACCESS/iceberg-2023/tables-iceberg-getting-started). ### Create an external volume diff --git a/website/docs/spark.md b/website/docs/spark.md index 7490c92a..876c0300 100644 --- a/website/docs/spark.md +++ b/website/docs/spark.md @@ -7,7 +7,7 @@ import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; # Querying from Apache Spark -To read a OneTable synced target table (regardless of the table format) in Apache Spark locally or on services like +To read a XTable synced target table (regardless of the table format) in Apache Spark locally or on services like Amazon EMR, Google Cloud's Dataproc, Azure HDInsight, or Databricks, you do not need additional jars or configs other than what is needed by the respective table formats. diff --git a/website/docs/starrocks.md b/website/docs/starrocks.md index 4f282cf0..de7c9afd 100644 --- a/website/docs/starrocks.md +++ b/website/docs/starrocks.md @@ -9,7 +9,7 @@ import TabItem from '@theme/TabItem'; # Querying from StarRocks StarRocks allows you to query table formats like Hudi, Delta and Iceberg tables using our [external catalog](https://docs.starrocks.io/docs/data_source/catalog/catalog_overview/) feature. -Users do not need additional configurations to work with OneTable synced tables. +Users do not need additional configurations to work with XTable synced tables. For more information and required configurations refer to: * [Hudi Catalog](https://docs.starrocks.io/docs/data_source/catalog/hudi_catalog/) @@ -17,7 +17,7 @@ For more information and required configurations refer to: * [Iceberg Catalog](https://docs.starrocks.io/docs/data_source/catalog/iceberg_catalog/) For hands on experimentation, please follow [Creating your first interoperable table](/docs/how-to#create-dataset) -to create OneTable synced tables followed by [Hive Metastore](/docs/hms) to register the target table +to create XTable synced tables followed by [Hive Metastore](/docs/hms) to register the target table in Hive Metastore. Once done, please follow the below high level steps: 1. Start the StarRocks server 2. From the directory where you have installed mysql-cli: login by running `mysql -P 9030 -h 127.0.0.1 -u root --prompt="StarRocks > "`. @@ -34,7 +34,7 @@ values={[ <TabItem value="hudi"> :::tip Note: -If you are following the example from [Hive Metastore](/docs/hms), you can query the OneTable synced Hudi table +If you are following the example from [Hive Metastore](/docs/hms), you can query the XTable synced Hudi table from StarRocks using the below query. ```sql md title="sql" CREATE EXTERNAL CATALOG unified_catalog_hms PROPERTIES ("type" = "unified","unified.metastore.type" = "hive", "hive.metastore.uris" = "thrift://hivemetastore:9083" ); @@ -46,7 +46,7 @@ SELECT * FROM unified_catalog_hms.hudi_db.<table_name>; <TabItem value="delta"> :::tip Note: -If you are following the example from [Hive Metastore](/docs/hms), you can query the OneTable synced Delta table +If you are following the example from [Hive Metastore](/docs/hms), you can query the XTable synced Delta table from StarRocks using the below query. ```sql md title="sql" CREATE EXTERNAL CATALOG unified_catalog_hms PROPERTIES ("type" = "unified","unified.metastore.type" = "hive", "hive.metastore.uris" = "thrift://hivemetastore:9083" ); @@ -58,7 +58,7 @@ SELECT * FROM unified_catalog_hms.delta_db.<table_name>; <TabItem value="iceberg"> :::tip Note: -If you are following the example from [Hive Metastore](/docs/hms), you can query the OneTable synced Iceberg table +If you are following the example from [Hive Metastore](/docs/hms), you can query the XTable synced Iceberg table from StarRocks using the below query. ```sql md title="sql" CREATE EXTERNAL CATALOG unified_catalog_hms PROPERTIES ("type" = "unified","unified.metastore.type" = "hive", "hive.metastore.uris" = "thrift://hivemetastore:9083" ); diff --git a/website/docs/trino.md b/website/docs/trino.md index d384679a..5ec91169 100644 --- a/website/docs/trino.md +++ b/website/docs/trino.md @@ -9,7 +9,7 @@ import TabItem from '@theme/TabItem'; # Querying from Trino Trino just like Presto allows you to query table formats like Hudi, Delta and Iceberg tables using connectors. -Users do not need additional configurations to work with OneTable synced tables. +Users do not need additional configurations to work with XTable synced tables. For more information and required configurations refer to: * [Hudi Connector](https://trino.io/docs/current/connector/hudi.html) @@ -17,7 +17,7 @@ For more information and required configurations refer to: * [Iceberg Connector](https://trino.io/docs/current/connector/iceberg.html) For hands on experimentation, please follow [Creating your first interoperable table](/docs/how-to#create-dataset) -to create OneTable synced tables followed by [Hive Metastore](/docs/hms) to register the target table +to create XTable synced tables followed by [Hive Metastore](/docs/hms) to register the target table in Hive Metastore. Once done, please follow the below high level steps: 1. Start the Trino server manually if you are working with a non-managed Trino service: from the trino-server directory run `./bin/launcher run` @@ -36,7 +36,7 @@ values={[ <TabItem value="hudi"> :::tip Note: -If you are following the example from [Hive Metastore](/docs/hms), you can query the OneTable synced Hudi table +If you are following the example from [Hive Metastore](/docs/hms), you can query the XTable synced Hudi table from Trino using the below query. ```sql md title="sql" SELECT * FROM hudi.hudi_db.<table_name>; @@ -47,7 +47,7 @@ SELECT * FROM hudi.hudi_db.<table_name>; <TabItem value="delta"> :::tip Note: -If you are following the example from [Hive Metastore](/docs/hms), you can query the OneTable synced Delta table +If you are following the example from [Hive Metastore](/docs/hms), you can query the XTable synced Delta table from Trino using the below query. ```sql md title="sql" SELECT * FROM delta.delta_db.<table_name>; @@ -58,7 +58,7 @@ SELECT * FROM delta.delta_db.<table_name>; <TabItem value="iceberg"> :::tip Note: -If you are following the example from [Hive Metastore](/docs/hms), you can query the OneTable synced Iceberg table +If you are following the example from [Hive Metastore](/docs/hms), you can query the XTable synced Iceberg table from Trino using the below query. ```sql md title="sql" SELECT * FROM iceberg.iceberg_db.<table_name>; diff --git a/website/docs/unity-catalog.md b/website/docs/unity-catalog.md index fff98d27..ce06f5e8 100644 --- a/website/docs/unity-catalog.md +++ b/website/docs/unity-catalog.md @@ -4,7 +4,7 @@ title: "Unity Catalog" --- # Syncing to Unity Catalog -This document walks through the steps to register a OneTable synced Delta table in Unity Catalog on Databricks. +This document walks through the steps to register a XTable synced Delta table in Unity Catalog on Databricks. ## Pre-requisites 1. Source table(s) (Hudi/Iceberg) already written to external storage locations like S3/GCS/ADLS. @@ -16,12 +16,12 @@ This document walks through the steps to register a OneTable synced Delta table * Follow the steps outlined [here](https://docs.databricks.com/en/storage/azure-storage.html) for Azure Data Lake Storage Gen2 and Blob Storage. 3. Create a Unity Catalog metastore in Databricks as outlined [here](https://docs.gcp.databricks.com/data-governance/unity-catalog/create-metastore.html#create-a-unity-catalog-metastore). 4. Create an external location in Databricks as outlined [here](https://docs.databricks.com/en/sql/language-manual/sql-ref-syntax-ddl-create-location.html). -5. Clone the OneTable [repository](https://github.com/onetable-io/onetable) and create the +5. Clone the XTable [repository](https://github.com/onetable-io/onetable) and create the `utilities-0.1.0-SNAPSHOT-bundled.jar` by following the steps on the [Installation page](/docs/setup) ## Steps ### Running sync -Create `my_config.yaml` in the cloned OneTable directory. +Create `my_config.yaml` in the cloned XTable directory. ```yaml md title="yaml" sourceFormat: HUDI|ICEBERG # choose only one @@ -39,7 +39,7 @@ datasets: 2. And replace with appropriate values for `sourceFormat`, and `tableName` fields. ::: -From your terminal under the cloned OneTable directory, run the sync process using the below command. +From your terminal under the cloned XTable directory, run the sync process using the below command. ```shell md title="shell" java -jar utilities/target/utilities-0.1.0-SNAPSHOT-bundled.jar --datasetConfig my_config.yaml @@ -77,6 +77,6 @@ SELECT * FROM onetable.synced_delta_schema.<table_name>; ## Conclusion In this guide we saw how to, -1. sync a source table to create metadata for the desired target table formats using OneTable +1. sync a source table to create metadata for the desired target table formats using XTable 2. catalog the data in Delta format in Unity Catalog on Databricks 3. query the Delta table using Databricks SQL editor diff --git a/website/docusaurus.config.js b/website/docusaurus.config.js index fab6a6e4..285a51d4 100644 --- a/website/docusaurus.config.js +++ b/website/docusaurus.config.js @@ -6,7 +6,7 @@ const darkCodeTheme = require('prism-react-renderer/themes/dracula'); /** @type {import('@docusaurus/types').Config} */ const config = { - title: 'OneTable', + title: 'XTable', favicon: 'images/onetable_favicon.png', url: 'https://onetable.dev', baseUrl: '/', @@ -45,12 +45,12 @@ const config = { /** @type {import('@docusaurus/preset-classic').ThemeConfig} */ ({ navbar: { - title: 'OneTable', + title: 'XTable', logo: { - alt: 'OneTable Logo', + alt: 'XTable Logo', href: 'pathname:///', target: '_self', - src: 'images/OneTableLogo.png', + src: 'images/xtable.png', }, items: [ { diff --git a/website/static/css/onetable-ad267e.webflow.css b/website/static/css/onetable-ad267e.webflow.css index 020eb9ee..646985db 100644 --- a/website/static/css/onetable-ad267e.webflow.css +++ b/website/static/css/onetable-ad267e.webflow.css @@ -112,8 +112,8 @@ background-image: url('../images/GR-BG1.svg'), linear-gradient(135deg, #04548c, #043c74); background-position: 0 0, 0 0; background-size: auto, auto; - padding-top: 130px; - padding-bottom: 130px; + padding-top: 40px; + padding-bottom: 80px; } .hero-container { @@ -405,6 +405,16 @@ display: flex; } +.callout-section{ + padding: 10px; + background: beige; + color: var(--black); + text-align: center; + /* text-transform: uppercase; */ + /* margin-bottom: 40px; */ + font-size: 16px; + line-height: 22px; +} .logo-section { background-image: linear-gradient(#ecf1f4, #f7f7f8); padding-top: 120px; @@ -874,8 +884,12 @@ .image-8 { width: 100%; + height: 56px; +} +.xtable-title{ + height: 120px; + margin-bottom: 10px; } - .main-container-footer { max-width: 1200px; justify-content: space-between; @@ -2771,4 +2785,9 @@ font-weight: 700; font-style: italic; font-display: swap; +} + +.footer__bottom text--center{ + margin-left: 50px; + margin-right: 50px; } \ No newline at end of file diff --git a/website/static/images/apache-incubator.svg b/website/static/images/apache-incubator.svg 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a/website/static/images/xtable-words-white.png b/website/static/images/xtable-words-white.png new file mode 100644 index 00000000..7021d96b Binary files /dev/null and b/website/static/images/xtable-words-white.png differ diff --git a/website/static/images/xtable-words.png b/website/static/images/xtable-words.png new file mode 100644 index 00000000..f1401beb Binary files /dev/null and b/website/static/images/xtable-words.png differ diff --git a/website/static/images/xtable.png b/website/static/images/xtable.png new file mode 100644 index 00000000..43554889 Binary files /dev/null and b/website/static/images/xtable.png differ diff --git a/website/static/index.html b/website/static/index.html index 89fa9b35..5480983d 100644 --- a/website/static/index.html +++ b/website/static/index.html @@ -3,13 +3,13 @@ <html data-wf-page="65402b66d39d6454e51fabf1" data-wf-site="65402b66d39d6454e51fabed"> <head> <meta charset="utf-8"> - <title>OneTable</title> - <meta content="OneTable is an omni-directional interop of lakehouse table formats Apache Hudi, Apache Iceberg, and Delta Lake. OneTable is NOT a new or separate format, OneTable provides abstractions and tools for the translation of lakehouse table format metadata." name="description"> - <meta content="OneTable" property="og:title"> - <meta content="OneTable is an omni-directional interop of lakehouse table formats Apache Hudi, Apache Iceberg, and Delta Lake. OneTable is NOT a new or separate format, OneTable provides abstractions and tools for the translation of lakehouse table format metadata." property="og:description"> + <title>XTable</title> + <meta content="XTable is a cross-table interop of lakehouse table formats Apache Hudi, Apache Iceberg, and Delta Lake. XTable is NOT a new or separate format, XTable provides abstractions and tools for the translation of lakehouse table format metadata." name="description"> + <meta content="XTable" property="og:title"> + <meta content="XTable is a cross-table interop of lakehouse table formats Apache Hudi, Apache Iceberg, and Delta Lake. XTable is NOT a new or separate format, XTable provides abstractions and tools for the translation of lakehouse table format metadata." property="og:description"> <meta content="https://uploads-ssl.webflow.com/65402b66d39d6454e51fabed/654c643bf9cebe95d6c3dd50_Group%201562%20(1).png" property="og:image"> - <meta content="OneTable" property="twitter:title"> - <meta content="OneTable is an omni-directional interop of lakehouse table formats Apache Hudi, Apache Iceberg, and Delta Lake. OneTable is NOT a new or separate format, OneTable provides abstractions and tools for the translation of lakehouse table format metadata." property="twitter:description"> + <meta content="XTable" property="twitter:title"> + <meta content="XTable is a cross-table interop of lakehouse table formats Apache Hudi, Apache Iceberg, and Delta Lake. XTable is NOT a new or separate format, XTable provides abstractions and tools for the translation of lakehouse table format metadata." property="twitter:description"> <meta content="https://uploads-ssl.webflow.com/65402b66d39d6454e51fabed/654c643bf9cebe95d6c3dd50_Group%201562%20(1).png" property="twitter:image"> <meta property="og:type" content="website"> <meta content="summary_large_image" name="twitter:card"> @@ -29,7 +29,7 @@ <body class="body"> <div data-animation="default" data-collapse="medium" data-duration="400" data-easing="ease" data-easing2="ease" role="banner" class="navbar w-nav"> <div class="container w-container"> - <a href="#" class="brand w-nav-brand"><img src="images/nav-logo.png" loading="lazy" alt="" class="nav-logo"></a> + <a href="#" class="brand w-nav-brand"><img src="images/xtable-white.png" loading="lazy" alt="" class="nav-logo"></a> <nav role="navigation" class="nav-menu w-nav-menu"> <a href="#" class="nav-link w-nav-link">Home</a> <a href="https://onetable.dev/docs/setup/"; class="nav-link w-nav-link">Docs</a> @@ -45,7 +45,7 @@ </div> <div data-animation="default" data-collapse="medium" data-duration="400" data-easing="ease" data-easing2="ease" role="banner" class="navbar-copy w-nav"> <div class="container-copy w-container"> - <a href="#" class="brand-copy w-nav-brand"><img src="images/nav-logo.png" loading="lazy" alt="" class="nav-logo-copy"></a> + <a href="#" class="brand-copy w-nav-brand"><img src="images/xtable-white.png" loading="lazy" alt="" class="nav-logo-copy"></a> <nav role="navigation" class="nav-menu-copy w-nav-menu"> <a href="#" class="nav-link-copy w-nav-link">Home</a> <a href="https://onetable.dev/docs/setup/"; class="nav-link-copy w-nav-link">Docs</a> @@ -62,14 +62,19 @@ <section class="hero-section"> <div class="w-layout-blockcontainer hero-container w-container"> <div class="left-hero"> - <h1 class="hero-heading">OneTable</h1> - <div class="hero-textblock">Seamlessly interoperate between Apache Hudi, Delta Lake, and Apache Iceberg.</div> + <img src="images/xtable-words-white.png" loading="lazy" alt="" class="xtable-title"> + <div class="hero-textblock">Seamlessly interoperate cross-table between Apache Hudi, Delta Lake, and Apache Iceberg</div> <div class="button-group"> <a href="https://github.com/onetable-io/onetable"; class="primary-button w-button">Try it on GitHub</a> <a href="https://onetable.dev/docs/setup/"; class="secondary-button w-button">Learn More</a> </div> </div> - <div class="right-hero"><img src="images/Onetable-logo.png" loading="lazy" alt="" class="hero-image"></div> + <div class="right-hero"><img src="images/xtable-hero.svg" loading="lazy" alt="" class="hero-image"></div> + </div> + </section> + <section class="callout-section"> + <div class="w-layout-blockcontainer container-main w-container"> + Apache XTable is incubating in the Apache Software Foundation and was recently renamed from OneTable </div> </section> <section class="logo-section"> @@ -85,10 +90,11 @@ <section class="what-section"> <div class="w-layout-blockcontainer main-container-why w-container"> <div class="up-section-why"> - <h1 class="heading-section why">What is<span class="text-span"> OneTable?</span></h1> + <h1 class="heading-section why">What is<span class="text-span"> XTable?</span></h1> <ul role="list" class="list"> - <li class="list-item why">Onetable provides omni-directional interop between lakehouse table formats</li> - <li class="list-item why">OneTable is NOT a new or separate format, OneTable provides abstractions and tools for the translation of lakehouse table format metadata</li> + <li class="list-item why">XTable provides cross-table omni-directional interop between lakehouse table formats</li> + <li class="list-item why">XTable is NOT a new or separate format, XTable provides abstractions and tools for the translation of lakehouse table format metadata</li> + <li class="list-item why">XTable is formerly known as OneTable</li> </ul> </div> <div id="w-node-b5fb012b-3ce1-44e6-09e8-015167aa018f-e51fabf1" class="w-layout-layout quick-stack wf-layout-layout"> @@ -99,29 +105,7 @@ <div class="what-text">Choose your <span class="text-span-3">destination</span> format(s)</div> </div> <div id="w-node-a5b4b7dd-251e-d9a7-855d-46427e19ad9b-e51fabf1" class="w-layout-cell what-cell"><img src="images/metadata-1.png" loading="lazy" alt="" class="image-4"> - <div class="what-text">Onetable will translate the <span class="text-span-3">Metadata</span> layers</div> - </div> - </div> - </div> - </section> - <section class="what-section-copy"> - <div class="w-layout-blockcontainer main-container-why-copy w-container"> - <div class="up-section-why-copy"> - <h1 class="heading-section-copy why-copy">What is<span class="text-span"> OneTable?</span></h1> - <ul role="list" class="list-copy"> - <li class="list-item why">OneTable is an omni-directional interop of lakehouse table formats</li> - <li class="list-item why">OneTable is NOT a new or separate format, OneTable provides abstractions and tools for the translation of lakehouse table format metadata</li> - </ul> - </div> - <div id="w-node-c7411165-6ba1-6089-10bd-ef98a599082e-e51fabf1" class="w-layout-layout quick-stack-copy wf-layout-layout"> - <div id="w-node-c7411165-6ba1-6089-10bd-ef98a599082f-e51fabf1" class="w-layout-cell what-cell-copy"><img src="images/source1.svg" loading="lazy" alt="" class="image-6-copy"> - <div class="what-text-copy">Choose your <span class="text-span-3-copy">source</span> format</div> - </div> - <div id="w-node-c7411165-6ba1-6089-10bd-ef98a5990836-e51fabf1" class="w-layout-cell what-cell-copy"><img src="images/destination1.svg" loading="lazy" alt="" class="image-5-copy"> - <div class="what-text-copy">Choose your <span class="text-span-3-copy">destination</span> format(s)</div> - </div> - <div id="w-node-c7411165-6ba1-6089-10bd-ef98a599083d-e51fabf1" class="w-layout-cell what-cell-copy"><img src="images/metadata1.svg" loading="lazy" alt="" class="image-4-copy"> - <div class="what-text-copy">Onetable will translate the <span class="text-span-3-copy">Metadata</span> layers</div> + <div class="what-text">XTable will translate the <span class="text-span-3">Metadata</span> layers</div> </div> </div> </div> @@ -129,7 +113,7 @@ <section class="build-section"> <div class="w-layout-blockcontainer main-container w-container"> <div class="left-section"> - <h1 class="heading-section">Why <span class="text-span">build</span> OneTable?</h1> + <h1 class="heading-section">Why <span class="text-span">build</span> XTable?</h1> <ul role="list" class="list"> <li class="list-item">Choosing a table format is a costly evaluation</li> <li class="list-item">Each project has rich features that may fit different use-cases</li> @@ -137,7 +121,7 @@ <li class="list-item">Your data should be <span class="text-span-2">UNIVERSAL</span></li> </ul> </div> - <div class="right-section"><img src="images/Group-1562-1.png" loading="lazy" sizes="(max-width: 479px) 91vw, (max-width: 767px) 71vw, (max-width: 991px) 64vw, 43vw" srcset="images/Group-1562-1-p-500.png 500w, images/Group-1562-1-p-800.png 800w, images/Group-1562-1-p-1080.png 1080w, images/Group-1562-1.png 1311w" alt="" class="image-3"></div> + <div class="right-section"><img src="images/write-query.png" loading="lazy" sizes="(max-width: 479px) 91vw, (max-width: 767px) 71vw, (max-width: 991px) 64vw, 43vw" srcset="images/Group-1562-1-p-500.png 500w, images/Group-1562-1-p-800.png 800w, images/Group-1562-1-p-1080.png 1080w, images/Group-1562-1.png 1311w" alt="" class="image-3"></div> </div> </section> <section class="together-section"> @@ -146,7 +130,7 @@ <div class="div-block-24"> <div class="right-section-together"> <h1 class="heading-section-together">Let's <span class="text-span">build together</span></h1> - <div class="text-block">OneTable is a community driven open source project. Come join us on Github and find easy ways to contribute.</div> + <div class="text-block">XTable is a community driven open source project. Come join us on Github and find easy ways to contribute.</div> </div> <a href="https://github.com/onetable-io/onetable"; class="primary-button w-button">Try it on GitHub</a> </div> @@ -165,34 +149,34 @@ <div class="icon-2 accordion-icon">keyboard_arrow_down</div> </div> <div class="accordion-item-content"> - <p class="faq-a">OneTable reads the existing metadata of your table and writes out metadata for one or more other table formats by leveraging the existing APIs provided by each table format project. The metadata will be persisted under a directory in the base path of your table (_delta_log for Delta, metadata for Iceberg, and .hoodie for Hudi). This allows your existing data to be read as though it was written using Delta, Hudi, or Iceberg. For example, a Spark reader can use [...] + <p class="faq-a">XTable reads the existing metadata of your table and writes out metadata for one or more other table formats by leveraging the existing APIs provided by each table format project. The metadata will be persisted under a directory in the base path of your table (_delta_log for Delta, metadata for Iceberg, and .hoodie for Hudi). This allows your existing data to be read as though it was written using Delta, Hudi, or Iceberg. For example, a Spark reader can use s [...] </div> </div> <div class="accordion-item"> <div id="q1" class="accordion-item-trigger"> - <h4 class="accordion-heading"><span><strong class="faq-q">How is OneTable different from Delta Lake Uniform?</strong></span></h4> + <h4 class="accordion-heading"><span><strong class="faq-q">How is XTable different from Delta Lake Uniform?</strong></span></h4> <div class="icon-2 accordion-icon">keyboard_arrow_down</div> </div> <div class="accordion-item-content"> - <p class="faq-a">OneTable provides abstraction interfaces that allow omni-directional interoperability across Delta, Hudi, Iceberg, and any other future lakehouse table formats such as Apache Paimon. OneTable is a standalone github project that provides a neutral space for all the lakehouse table formats to constructively collaborate together.<br><br>Delta Lake Uniform is a one-directional conversion from Delta Lake to Apache Hudi or Apache Iceberg. Uniform is also governed i [...] + <p class="faq-a">XTable provides abstraction interfaces that allow omni-directional interoperability across Delta, Hudi, Iceberg, and any other future lakehouse table formats such as Apache Paimon. XTable is a standalone github project that provides a neutral space for all the lakehouse table formats to constructively collaborate together.<br><br>Delta Lake Uniform is a one-directional conversion from Delta Lake to Apache Hudi or Apache Iceberg. Uniform is also governed insid [...] </div> </div> <div class="accordion-item"> <div id="q1" class="accordion-item-trigger"> - <h4 class="accordion-heading"><span><strong class="faq-q">When should I consider OneTable?</strong></span></h4> + <h4 class="accordion-heading"><span><strong class="faq-q">When should I consider XTable?</strong></span></h4> <div class="icon-2 accordion-icon">keyboard_arrow_down</div> </div> <div class="accordion-item-content"> - <p class="faq-a">OneTable can be used to easily switch between any of the table formats or even benefit from more than one simultaneously. Some organizations use OneTable today because they have a diverse ecosystem of tools with polarized vendor support of table formats. Some users want lightning fast ingestion or indexing from Hudi and photon query accelerations of Delta Lake inside of Databricks. Some users want managed table services from Hudi, but also want write operatio [...] + <p class="faq-a">XTable can be used to easily switch between any of the table formats or even benefit from more than one simultaneously. Some organizations use XTable today because they have a diverse ecosystem of tools with polarized vendor support of table formats. Some users want lightning fast ingestion or indexing from Hudi and photon query accelerations of Delta Lake inside of Databricks. Some users want managed table services from Hudi, but also want write operations f [...] </div> </div> <div class="accordion-item"> <div id="q1" class="accordion-item-trigger"> - <h4 class="accordion-heading"><span><strong class="faq-q">Does OneTable work in every cloud?</strong></span></h4> + <h4 class="accordion-heading"><span><strong class="faq-q">Does XTable work in every cloud?</strong></span></h4> <div class="icon-2 accordion-icon">keyboard_arrow_down</div> </div> <div class="accordion-item-content"> - <p class="faq-a">Yes, anywhere that Delta, Iceberg, or Hudi work, OneTable works.</p> + <p class="faq-a">Yes, anywhere that Delta, Iceberg, or Hudi work, XTable works.</p> </div> </div> <div class="accordion-item"> @@ -201,7 +185,7 @@ <div class="icon-2 accordion-icon">keyboard_arrow_down</div> </div> <div class="accordion-item-content"> - <p class="faq-a">1. Hudi and Iceberg MoR tables not supported<br>2. Delta Delete Vectors are not supported<br>3. Synchronized transaction timestamps<br><br>With OneTable you pick one primary format and one or more secondary formats. The write operations with the primary format work as normal. OneTable than translates the metadata from the primary format to the secondaries. When committing the metadata of the secondary formats, the timestamp of the commit will not be the exact [...] + <p class="faq-a">1. Hudi and Iceberg MoR tables not supported<br>2. Delta Delete Vectors are not supported<br>3. Synchronized transaction timestamps<br><br>With XTable you pick one primary format and one or more secondary formats. The write operations with the primary format work as normal. XTable than translates the metadata from the primary format to the secondaries. When committing the metadata of the secondary formats, the timestamp of the commit will not be the exact sam [...] </div> </div> <div class="accordion-item"> @@ -219,7 +203,7 @@ <div class="icon-2 accordion-icon">keyboard_arrow_down</div> </div> <div class="accordion-item-content"> - <p class="faq-a">Follow OneTable community channels on Linkedin and Twitter. Become a watcher on Github or reachout directly to any of the Github contributors to learn more.</p> + <p class="faq-a">Follow XTable community channels on Linkedin and Twitter. Become a watcher on Github or reachout directly to any of the Github contributors to learn more.</p> </div> </div> <div class="accordion-item"> @@ -228,7 +212,7 @@ <div class="icon-2 accordion-icon">keyboard_arrow_down</div> </div> <div class="accordion-item-content"> - <p class="faq-a">Current contributors across Onehouse, Microsoft, Google, and others are planning to incubate OneTable into the Apache Software Foundation. Stay tuned for more updates.</p> + <p class="faq-a">Current contributors across Onehouse, Microsoft, Google, and others are planning to incubate XTable into the Apache Software Foundation. Stay tuned for more updates.</p> </div> </div> </div> @@ -236,14 +220,21 @@ </div> <section class="footer-subscribe"> <div class="main-container-footer"> - <div class="div-block-25"><img src="images/OneTable-F.png" loading="lazy" alt="" class="image-8"></div> + <div class="div-block-25"><img src="images/xtable-white.png" loading="lazy" alt="" class="image-8"></div> <div class="footer-block-three"> <a href="https://onetable.dev/docs/setup/"; class="footer-link-three">Docs</a> <a href="https://github.com/onetable-io/onetable"; class="footer-link-three">GitHub</a> <a href="https://www.linkedin.com/company/onetable-oss/"; class="footer-link-three">LinkedIn</a> <a href="https://twitter.com/OnetableOSS"; class="footer-link-three l">Twitter</a> </div> - <div class="footer-copyright"> </div> + </div> + <div class="footer__bottom text--center"><div class="footer__copyright" style="color: white;text-align: center;"> + <div style="margin-top: 20px"> + <a href="https://incubator.apache.org/"; target="_blank"><img style="height:40px; margin-bottom: 10px; margin-top: 10px" alt="Apache Software Foundation" src="/images/apache-incubator.svg"></a> + <p style="text-align:left; font-weight: 300; font-size: 0.8em;">Apache XTable is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the c [...] + <p style="text-align:left; font-weight: 300; font-size: 0.8em;">Copyright ©2024 Apache XTable, XTable, Apache, the Apache feather logo and the Apache XTable project logo are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.</p> + </div> + </div> </div> </section> <script src="https://d3e54v103j8qbb.cloudfront.net/js/jquery-3.5.1.min.dc5e7f18c8.js?site=65402b66d39d6454e51fabed"; type="text/javascript" integrity="sha256-9/aliU8dGd2tb6OSsuzixeV4y/faTqgFtohetphbbj0=" crossorigin="anonymous"></script>
