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DuckDB

Summary: Notes on DuckDB and its use for analytical and geospatial data processing. Last updated: 2026-08-20

2026

  • Optimizing DuckDB Spatial Queries: A technical deep-dive comparing spatial join performance between PostGIS and DuckDB, explaining how DuckDB's R-tree index fires only for single constant geometry comparisons while PostGIS auto-uses its GiST index — and showing that DuckDB's streaming SPATIAL_JOIN operator wins at scale when both datasets are large. Related: SQL. Keywords: DuckDB, PostGIS, spatial queries, R-tree, GiST, spatial join, performance, geospatial

  • spatial-access-measures: Web map using DuckDB-WASM and GeoParquet for in-browser SQL queries and filtering of Statistics Canada spatial access measures (transit, cycling, and walking accessibility to jobs, schools, and services). No server backend required — everything runs in the browser. Demo Related: CNG, Web_Mapping, Tools. Keywords: DuckDB-WASM, GeoParquet, deck.gl, in-browser SQL, accessibility, Canada, cloud-native

  • Freestiler: R and Python tool for creating PMTiles vector tilesets from spatial data, including from DuckDB SQL queries. Uses a Rust tiling engine for in-process performance, producing single .pmtiles files compatible with Mapbox and MapLibre formats. Related: Web_Mapping, Python, CNG. Keywords: PMTiles, DuckDB, R, Python, vector tiles, cloud-native, MapLibre, geospatial

  • GeoParquet Writing Cookbook: A practical guide with best practices and recipes for creating GeoParquet files using tools like GDAL, DuckDB, and geopandas, covering encoding strategies and optimization techniques for cloud-native geospatial workflows. Related: CNG, Remote_Sensing, Python. Keywords: GeoParquet, DuckDB, GDAL, cloud-native, geospatial, spatial queries, Python