Vortex Support in DuckDB

Summary

Announcing Vortex Support in DuckDB Guillermo Sanchez, SpiralDB Team 2026-01-23 · 8 min TL;DR: Vortex is a new columnar file format with a very promising design. SpiralDB and DuckDB Labs have partnered to give you a very fast experience while reading and writing Vortex files! I think it is worth starting this intro by talking a little bit about the established format for columnar data. Parquet has done some amazing things for analytics. If you go back to the times where CSV was the better alternative, then you know how important Parquet is. However, even if the specification has evolved over time, Parquet has some design constraints. A particular limitation is that it is block-compressed and engines need to decompress pages in order to do further operations like filtering, decoding values, etc. For a while, researchers and private companies have been working on alternatives to Parquet that could improve on some of Parquet’s shortcomings. Vortex, from the SpiralDB team, is one of them. Vortex is an extensible, open source format for columnar data. It was created to handle heterogeneous compute patterns and different data modalities. But, what does this mean? The project was donated to the Linux Foundation by the SpiralDB team in August 2025. Vortex provides different layouts and encodings for different data types. Some of the most notorious are ALP for floating point encoding or FSST for string encoding. This lightweight compression strategy keeps data sizes down while allowing one of Vortex’s most important features: compute functions. By knowing the encoded layout of the data, Vortex is able to run arbitrary expressions on compressed data. This allows a Vortex reader to execute, for example, filter expressions within storage segments without decompressing data. We mentioned heterogeneous compute to emphasize that Vortex was designed with the idea of having optimized layouts for different data types, including vectors, large text or even image or audio, but also to ...