DuckDB's columnar tricks, tried on an eval log: query files in place, ASOF joins, sorted Parquet
DuckDB's team explains why storing data by column makes it fast. We tried the ideas on a small LLM eval log, with short queries you can run in a minute.
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DuckDB's team explains why storing data by column makes it fast. We tried the ideas on a small LLM eval log, with short queries you can run in a minute.
DuckDB 2.0.0 is out with Quack client-server, async I/O for S3, VARIANT, agent mode and triggers. Support runs to October 2027. Test before you upgrade.
DuckDB's v2.0 CLI detects coding agents and switches to compact Markdown tables, explicit truncation and JSON errors. DuckDB says agent output fell 59%, about 0.5% of total input tokens.
Polars 2.0, published 6 October, enables an initial spill-to-disk path and treats SQL as first class. Its TPC-H and TPC-DS-derived times against named DuckDB and DataFusion builds are Polars' own runs.
AWS GA’d direct Iceberg/Parquet lake queries from Aurora PostgreSQL (2026-09-30) via embedded DuckDB and aurora_analytics—no ETL. Join live ops rows (incl. uncommitted) with the lake. PG 17.11+/18.6+; no extra feature fee (compute + S3).