Editions

The whole tool is free.

Everything Flow Studio does today is in the open-source Community edition. The Enterprise edition will add what organisations need around it — and nothing already published will be taken away.

Community

Free · AGPL-3.0

For individuals, small teams, research groups and classrooms.

  • Visual canvas with Python and SQL nodes
  • pandas, Polars and DuckDB engines, plus SQL and Ibis pushdown to your warehouse
  • Every connector: PostgreSQL, MySQL, SQL Server, Oracle, ClickHouse, Snowflake, BigQuery, Redshift, Trino, Databricks, StarRocks, Doris, Druid, SQLite, Azure Data Lake, Delta Lake, Iceberg
  • Explore: drag-and-drop charts over flows and live databases
  • Native bulk loading, scheduling with retries and alerts, run history
  • Plugin system with isolated environments
  • AI-assisted authoring with your own model
  • Self-hosted with Docker
Get started

Enterprise

Coming

For organisations running Flow Studio as a shared service.

  • Single sign-on and roles — sign in with your identity provider; viewers, editors and administrators
  • Scaling across machines — run many flows and many users concurrently with distributed workers
  • Curated plugin bundles — tested, version-pinned environments for machine learning and scientific libraries
  • Data catalog for AI tools — your tables, profiles and lineage exposed to AI assistants over MCP
  • Support — from the people who build it
Register interest

Tell us what you'd need.

No sales calls, no commitment — this decides what gets built first.

Which capabilities matter

Used only to contact you about Flow Studio Enterprise. Ask and we'll delete it.

Questions

Will features move from Community to Enterprise?

No. Everything published in the open repository stays there. Enterprise adds new capabilities on top.

Why AGPL?

It keeps the project open: anyone can use, modify and self-host Flow Studio freely, and anyone offering a modified version as a network service shares their changes.

Is my data sent anywhere?

No. Flow Studio runs on your infrastructure. AI assistance only contacts the model provider you configure, and you can use a local one.

Something else? Ask on GitHub.