#5252nd of 102 in Backends, databases and hostingFor data and documents, data analysis
databend
Rust data warehouse with SQL analytics, vector and full-text search on object storage
- Stars
- 9.5k
- License
- Apache-2.0
- Last commit
- Nov 2026
- Last release
- Apr 2026
- Language
- Rust
9,197 on 21 Apr 20269,493 on 10 Nov 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
Databend is a data warehouse written in Rust that stores tables on object storage (S3, Azure, GCS). It runs SQL analytics, vector search via VECTOR INDEX, and full-text search via INVERTED INDEX on the same tables. It also supports Python UDFs run in sandbox workers and Git-like data branching, so agent workloads can run from SQL.
Who it is for: Teams needing one SQL warehouse for analytics, vector search and agent data
Strengths
- Vector, full-text and analytic queries run on the same table without a second system
- Compute is separate from storage on S3, Azure Blob or GCS
- Python UDFs run in sandbox workers and are called from plain SQL
- Published TPC-H and search benchmarks, each with SQL to reproduce
Weaknesses
- Published benchmarks were run on Databend Cloud, not on self-hosted clusters
- Some enterprise features are under Elastic 2.0, not Apache 2.0
- Sandbox UDF needs separate sandbox workers; self-hosted setup is not covered in the README
- Branching is mentioned but has no usage example in the README
What it needs
- Docker + Compose
- Needs Object storage (S3, Azure Blob, GCS), BendSQL client
- port 8000
Quick answers
Is databend open source?
Yes. Its code is on GitHub under the Apache-2.0 license.
Can you run databend with Docker?
Yes. Its repository has a Docker setup: a Dockerfile, a Compose file or a published image.
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