🎉 Apache Sedona 1.9.1 已正式发布！🗺️ 新增 Geography SQL 函数、Box2D 与 Box3D 类型、栅格 Python UDF 等。查看发布说明 →

The official source for Apache Sedona news, technical insights, release updates, and best practices in large-scale spatial data management.

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Seven Lines of NumPy, 121 Million Pixels

Those deep-green grids are California's Central Valley — some of the most intensively farmed land on Earth, not as a camera sees it but as the NDVI vegetation index does: computed, pixel by pixel, by seven lines of NumPy. Sedona ran those seven lines on 484 satellite tiles in parallel, straight out of a public S3 bucket, and wrote the answer back as Cloud Optimized GeoTIFFs. That's the new move in Sedona 1.9.1: a plain Python UDF can take raster columns and return rasters. If the raster function you need isn't built in — your index, your QA rule, your model — write it.

Five NDVI tiles computed by the seven-line Python UDF — deep-green field grids, blue canals, sandy rangeland, a city — above the UDF's code on a card

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Index a Million Rasters Without Reading a Pixel

Every raster team has the bucket. Thousands of GeoTIFFs accumulated from surveys, vendors, and pipelines — and no catalog. Which files cover this area? Which CRS are they in? Which ones were never converted to Cloud Optimized GeoTIFF? Until now, answering meant crawling the bucket with one-off scripts — or pulling rasters down just to inspect them.

Real Sentinel-2 scenes above the metadata card Sedona actually read — index a million rasters, read zero pixels

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Your Map Has Hotspots. Prove It.

Anyone can look at a map and see clumps. The interesting questions are the ones eyeballing can't answer: is that clustering statistically real? Exactly where is it significant? And which points genuinely don't belong?

Your map has hotspots — prove it: a field of grid cells with one glowing, statistically significant hotspot, and Sedona's spatial statistics toolkit named beneath

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OpenStreetMap, Meet Sedona: Raw .osm.pbf to Spatial SQL

OpenStreetMap is the world's map — every road, café, and coastline, edited by millions of people. It ships as .osm.pbf: a dense, compressed Protocol-Buffers blob of nodes, ways, and relations. Getting that into a cluster usually means a preprocessing detour through osmium or a staging database.

Apache Sedona reads a raw .osm.pbf file straight into a Sedona DataFrame, turning OpenStreetMap nodes, ways, and relations into points and lines

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SedonaDB 0.4.0 Release

The Apache Sedona community is excited to announce the release of SedonaDB version 0.4.0!

SedonaDB is the first open-source, single-node analytical database engine that treats spatial data as a first-class citizen. It is developed as a subproject of Apache Sedona. This release consists of 187 resolved issues including 26 new functions from 15 contributors.

Apache Sedona powers large-scale geospatial processing on distributed engines like Spark (SedonaSpark), Flink (SedonaFlink), and Snowflake (SedonaSnow). SedonaDB extends the Sedona ecosystem with a single-node engine optimized for small-to-medium data analytics, delivering the simplicity and speed that distributed systems often cannot.

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SedonaDB 0.3.0 Release

The Apache Sedona community is excited to announce the release of SedonaDB version 0.3.0!

SedonaDB is the first open-source, single-node analytical database engine that treats spatial data as a first-class citizen. It is developed as a subproject of Apache Sedona. This release consists of 187 resolved issues including 36 new functions from 18 contributors.

Apache Sedona powers large-scale geospatial processing on distributed engines like Spark (SedonaSpark), Flink (SedonaFlink), and Snowflake (SedonaSnow). SedonaDB extends the Sedona ecosystem with a single-node engine optimized for small-to-medium data analytics, delivering the simplicity and speed that distributed systems often cannot.

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Apache Sedona 2025 Year in Review

2025 was a milestone year for Apache Sedona. We made major progress in distributed spatial analytics on Spark, Flink, and Snowflake, launched a new single-node engine called SedonaDB, and pushed forward benchmarking and open geospatial data standards.

This post summarizes the most important highlights from the Apache Sedona ecosystem in 2025.