Databend

Databend is an enterprise data warehouse written in Rust that keeps analytics, vector search and full-text search inside one engine. Teams stop shuttling data between a warehouse, a vector store and a search index just to answer different kinds of questions.

Agent logic runs inside the warehouse through sandbox user defined functions. A control plane handles resource scheduling, permission validation and sandbox lifecycle, the execution plane orchestrates with SQL and issues requests over Arrow Flight, and isolated sandbox workers run your Python. Defining such a function and calling it across a table of tasks is ordinary SQL.

The engine is shaped by what enterprise workloads keep asking of it.

• Core analytics: large-scale SQL queries, transactions and automatic schema evolution.
• Search: vector and full-text search living beside the analytical tables.
• Branching: git-like data versioning so agents work on production snapshots safely.
• Elastic compute: cloud native scaling with S3, Azure or GCS underneath.
• Python sandboxes: isolated workers for agent logic, model calls and tool use.

Starting takes one of three forms, a managed cloud account, a local Python driver install for development on Python 3.12 or 3.13, or a Docker image that runs the full warehouse on your machine. Licensing splits between Apache 2.0 and Elastic 2.0 depending on the component.