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Awesome DuckDB Spatial Awesome

Long list of geospatial analysis tools. Geospatial analysis, or just spatial analysis, is an approach to applying statistical analysis and other analytic techniques to data which has a geographical or spatial aspect.

DuckDB_Spatial_Awesome

Awesome DuckDB Geospatial

A curated list of resources related to DuckDB’s geospatial capabilities (the spatial extension and related ecosystem): docs, tutorials, benchmarks, repos, integrations, videos, and community discussions.

DuckDB’s spatial extension brings PostGIS-like spatial SQL to an in-process OLAP engine, with built-in support for many vector formats via GDAL and a growing ecosystem of community extensions (e.g., H3).


Contents


Official


Core docs: functions & I/O


Blog posts & articles


Performance, indexing & optimization


Interoperability (PostGIS, GDAL, tooling)


Community extensions (H3, A5, etc.)


Repositories & tools


Web / WASM / Browser


Servers & APIs

  • duckdb_featureserv (GitHub) - OGC API Features server on top of DuckDB spatial (good base for WFS-like services).
  • tobilg/duckdb-tileserver - Lightweight Mapbox Vector Tile (MVT) tileserver for DuckDB + duckdb-spatial (Go), useful once your data lives in DuckDB tables/views.

Books & courses


Talks & videos


Community discussions


Libraries & Frameworks

Python

  • kraina-ai/quackosm - Read OpenStreetMap PBF with DuckDB, extract/filter, and produce analytics-friendly outputs (GeoParquet workflows).
  • ajl2718/whereabouts - Fast local geocoding in Python that uses DuckDB as its query engine (no external geocoding API required).
  • duckdb-extension-spatial (PyPI) - Helper package for installing/loading the DuckDB spatial extension from Python environments.

R

  • cidree/duckspatial - R package bridging {sf} with DuckDB spatial for memory-efficient vector analytics on large data.

“SQL-first” / DataFrame APIs


Visualization & GIS Integration


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A list of tools, pages, blog posts about DuckDB Spatial

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