DuckDB Internals: Columnar Storage, SQL Optimization, and Performance Architecture (Part 1)
By
Kyle Cheung
Summary
This article explores the internal architecture of DuckDB, explaining why it achieves high performance. It covers how DuckDB eliminates serialization overhead, parses and optimizes SQL queries, and stores data in columnar row groups with zone maps. The piece traces DuckDB's evolution from a 2019 research project at CWI Amsterdam to widespread adoption in notebooks, ETL pipelines, dashboards, and embedded analytics, with companies like MotherDuck, Hex, Omni, and Fivetran building products around it.
Source
Hacker NewsDuckDB Internals: Columnar Storage, SQL Optimization, and Performance Architecture (Part 1)greybeam.aiKey quotes
· 3 pulledDuckDB has gone from a research project at CWI Amsterdam in 2019 to one of the most widely adopted databases of the past decade.
The list of places it shows up is long: notebooks, ETL pipelines, dashboards, CI test runners, embedded analytics inside SaaS products, even an iPhone running TPC-H at scale factor 100.
Companies have started building real products around it.
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