DuckDB – Overview and latest developments
summary
DuckDB reports concrete growth and engineering work: 6M monthly Python downloads and the extensions ecosystem at 17M monthly installs. The 1.0 release ships stable, with no catastrophic bugs reported, and a preview shows features that work now: histogram(), query_table/table functions and SQL variables for dynamic SQL, unpacking columns, automatic CTE materialization, dynamic filter pushdown from joins, faster many-small-CSV reads, parallel streaming queries, geopar support, and new platforms (Windows ARM, Android, Pyodide). Community extensions use a C API roadmap and Rust support; funding comes from DuckDB Labs commercial contracts.
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chapters (16)
- 0:00Introduction
- 1:50State of DuckDB
- 3:16Fear of data and mission
- 4:44Three main use cases
- 7:13Adoption metrics
- 11:46Future overview
- 12:28Extensions and community
- 14:31Rust API plans
- 16:59PG DuckDB integration
- 18:01Eoni release highlights
- 22:38Eoni performance
- 24:44Automatic materialization of CTEs
- 26:08Streaming queries
- 27:14Spatial support updates
- 27:56Roadmap and Lakehouse
- 29:21Q&A
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