This is an automated email from the ASF dual-hosted git repository.
jiayu pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/sedona-db.git
The following commit(s) were added to refs/heads/main by this push:
new 175569d7 docs: Add PyPI download statistics badges to README and docs
homepage (#723)
175569d7 is described below
commit 175569d7f16783c8a3efa9295638a0876d3c74b5
Author: Jia Yu <[email protected]>
AuthorDate: Tue Mar 17 00:34:28 2026 -0700
docs: Add PyPI download statistics badges to README and docs homepage (#723)
---
README.md | 3 +++
docs/index.md | 3 +++
2 files changed, 6 insertions(+)
diff --git a/README.md b/README.md
index 7c458918..83714c66 100644
--- a/README.md
+++ b/README.md
@@ -19,6 +19,8 @@
# SedonaDB
+[](https://pypi.org/project/sedonadb/)
[](https://pepy.tech/project/sedonadb)
[](https://pepy.tech/project/sedonadb)
+
SedonaDB is an open-source single-node analytical database engine with
**geospatial as a first-class citizen**. It aims to deliver the fastest spatial
analytics query speed and the most comprehensive function coverage available.
SedonaDB is perfect for processing smaller to medium datasets on local
machines or cloud instances. For distributed workloads, you can leverage the
power of SedonaSpark, SedonaFlink, or SedonaSnow.
@@ -36,6 +38,7 @@ SedonaDB is perfect for processing smaller to medium datasets
on local machines
* **Spatial query optimization**
* Spatial-aware heuristic based optimization
* Spatial-aware cost based optimization
+ * Automatic disk spilling for large-scale spatial joins
* **Spatial query processing**
* Spatial range query, KNN query, spatial join query, KNN join query
diff --git a/docs/index.md b/docs/index.md
index 8dbac2c5..203b84d3 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -22,6 +22,8 @@ title: Introducing SedonaDB
under the License.
-->
+[](https://pypi.org/project/sedonadb/)
[](https://pepy.tech/project/sedonadb)
[](https://pepy.tech/project/sedonadb)
+
SedonaDB is an open-source single-node analytical database engine with
**geospatial as a first-class citizen**. It aims to deliver the fastest spatial
analytics query speed and the most comprehensive function coverage available.
SedonaDB is perfect for processing smaller to medium datasets on local
machines or cloud instances. For distributed workloads, you can leverage the
power of SedonaSpark, SedonaFlink, or SedonaSnow.
@@ -39,6 +41,7 @@ SedonaDB is perfect for processing smaller to medium datasets
on local machines
* **Spatial query optimization**
* Spatial-aware heuristic based optimization
* Spatial-aware cost based optimization
+ * Automatic disk spilling for large-scale spatial joins
* **Spatial query processing**
* Spatial range query, KNN query, spatial join query, KNN join query