Why DuckDB 2.0 is faster

kept by eddie oct 16

DuckDB 2.0 achieves speed gains through improved vectorized execution, better parallelism, and refined storage format, plus enhanced optimizer rules that reduce overhead and improve cache utilization.

Pandas Should Go Extinct
Pandas becomes inefficient beyond tens of gigabytes, but most analytics workloads stay under 100 GB and are better served by single‑machine tools like Polars or DuckDB.
also on DuckDB, #performance, #open-source, #developer-tools
The Grammar of Data: From Definition to Execution – Xorq
The article shows how xorq’s grammar of data lets you define a data pipeline once and execute it on DuckDB, DataFusion, or Snowflake without changes.
also on DuckDB, #open-source, #developer-tools