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databendlabs

databendlabs/databend

Open-source data warehouse written in Rust, combining SQL analytics, vector and full-text search, and Python UDF sandboxes on S3-compatible storage.

Open-source alternative to:SnowflakeElasticsearch

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What is it?

Databend is an enterprise data warehouse written in Rust. It runs analytics, vector search and full-text search in one engine, and supports automatic schema evolution and transactions. Data is stored on cloud object storage such as S3, Azure Blob and GCS.

The project targets AI agent workloads. Agent logic can be written as Python UDFs that execute in isolated sandbox workers, while SQL orchestrates when those functions run. A Git-like branching feature lets agents work on snapshots of production data without changing the source tables.

Databend can be tried through its cloud service, run locally with the Python driver's local mode, or started with a Docker image. Its SQL interface is exposed on port 8000 in the Docker setup.

Key features

  • 01Analytics, vector search and full-text search in a single engine.
  • 02Python sandbox UDFs executed in isolated workers.
  • 03SQL orchestration of agent logic via Arrow Flight.
  • 04Git-like data branching for safe experiments on production snapshots.
  • 05Automatic schema evolution and transactions.
  • 06Cloud-native storage on S3, Azure and GCS.

Use cases

  • Running AI agents against enterprise data with sandboxed Python logic.
  • Large-scale SQL analytics and BI workloads.
  • Building RAG pipelines that combine vector and full-text search.
  • Testing changes on a branch of production data before applying them.

Quick start

  1. 1

    Install the local Python driver

    pip install "databend-driver[local]>=0.34.0"
  2. 2

    Connect to a local database and run a query

    from databend_driver import connect conn = connect("databend+local:///./local-state") print(conn.query_row("SELECT 'Hello, Databend!'").values())
  3. 3

    Or run the full warehouse with Docker

    docker run -p 8000:8000 datafuselabs/databend

Things to know

  • The local Python mode requires Python 3.12 or 3.13 and databend-driver 0.34.0 or later.
  • Some enterprise features are under the Elastic 2.0 license rather than Apache 2.0.

Topics

#data-warehouse#sql#olap#vector-search#full-text-search#rust#lakehouse#ai-agents#ai#bigdata

FAQ

What is databend?
Open-source data warehouse written in Rust, combining SQL analytics, vector and full-text search, and Python UDF sandboxes on S3-compatible storage. Databend is an enterprise data warehouse written in Rust. It runs analytics, vector search and full-text search in one engine, and supports automatic schema evolution and transactions. Data is stored on cloud object storage such as S3, Azure Blob and GCS.
Is databend free to use? What license does it have?
databend is open source under the Apache-2.0 license. Check the license terms before using it in commercial products.
Is databend still maintained?
Actively maintained. The last commit to databend was on Oct 20, 2026.
What can I use databend for?
Running AI agents against enterprise data with sandboxed Python logic. Large-scale SQL analytics and BI workloads. Building RAG pipelines that combine vector and full-text search. Testing changes on a branch of production data before applying them.
How do I install databend?
Install the local Python driver: pip install "databend-driver[local]>=0.34.0" Connect to a local database and run a query: from databend_driver import connect conn = connect("databend+local:///./local-state") print(conn.query_row("SELECT 'Hello, Databend!'").values()) Or run the full warehouse with Docker: docker run -p 8000:8000 datafuselabs/databend
Where can I get databend?
The source code and installation instructions are on GitHub: https://github.com/databendlabs/databend

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