DuckDB is a free, open-source in-process analytics database. See how it works, its extension ecosystem, pricing, the MotherDuck cloud option, pros/cons, and…
DuckDB is a free, open-source, in-process SQL database engine built for fast analytical queries over large tabular datasets. Unlike client-server databases, it runs embedded directly inside an application, script, or notebook with no separate server to manage.
It was created by Mark Raasveldt and Hannes Muhleisen at CWI in Amsterdam and first released in 2019. A nonprofit DuckDB Foundation holds the project's intellectual property to keep it permanently MIT-licensed, while a related company, DuckDB Labs, provides paid commercial support.
DuckDB's columnar-vectorized execution engine processes batches of column values together rather than one row at a time, giving it substantial performance advantages over row-store databases for aggregations, joins, and scans over millions of rows.
It reads Parquet, CSV, and JSON files directly, including from cloud object storage like Amazon S3, and extends its capabilities through an official extension system covering spatial data, full-text search, and Excel files, with client libraries for Python, R, Java, Node.js, Go, Rust, and WebAssembly.
DuckDB itself is entirely free under the MIT license, with no usage limits, feature gating, or licensing fees for embedding it in any commercial or personal application.
Commercial support and custom development are available on negotiated terms from DuckDB Labs, while MotherDuck, a separate venture-backed company, sells a distinct paid, managed cloud service built on the DuckDB engine.
Yes. DuckDB is released under the MIT license and is completely free to use, with no usage limits.
No. MotherDuck is a separate, venture-backed company that offers a paid managed cloud service built on top of the open-source DuckDB engine.
It depends on the workload: DuckDB is built for analytical (OLAP) queries, while SQLite is optimized for transactional (OLTP) workloads, so many applications use both for different purposes.
Yes, through the official httpfs extension, DuckDB can query Parquet and CSV files stored in S3-compatible object storage directly.
DuckDB has official client libraries for Python, R, Java, Node.js, Go, Rust, C/C++, and WebAssembly.
DuckDB is maintained by its original creators through the nonprofit DuckDB Foundation, which holds the project's IP, and DuckDB Labs, a commercial consultancy staffed by the core engineers.