Introduction
Tabsdata is an open-source, distributed, horizontally scalable data integration platform that allows users to turn their Python functions into automated, AI-friendly workflows that move and transform data between a variety of different systems.
Built atop Kubernetes and the Polars DataFrame API, Tabsdata can be deployed on almost any machine that runs Python, requires no admin permissions or Docker dependency, and allows users to move and transform tabular data through an expression-based Pythonic interface.
Through Tabsdata's MCP integration, users can also use AI to build and analyze their workflows.
Key Features
Tabsdata can be deployed on almost any machine and requires only Python as a dependency.
See Architecture Overview for more detail on how these pieces fit together.
Next steps
- Install Tabsdata -- get the server running locally.
- Connect an AI Agent -- point your LLM at the MCP server.
- Run Your First Data Integration -- build a working flow end to end.
Community
You can join the Tabsdata community on Github or Slack.
Contributing
We appreciate all contributions, from reporting bugs to implementing new features. You can access the Tabsdata Github repository here.
License
For license information, see the Tabsdata website.