Integrating data

Integrate your full-stack applications with hosted Postgres tables or direct connections to your own data sources.

Data scientists & friends already have a lot of data places: your data warehouses, data lakes, data pipelines...but think of Baseten as your data vacation home. It has everything you need when you arrive, is close enough to a major airport to get anywhere you want to go, and offers all of the familiar comforts of home integrated into an exciting new environment. In less metaphorical terms, you have data tables ready to use with Baseten Postgres, you can bring your own sources with data connections, and surface your data for applications and analytics via the query builder.

Consider a simple, common example: you need to store the inputs and outputs of a predictive model every time you run it, along with associated data like when the model run occurred, the model's confidence in the prediction, and the user who triggered the model run. This documentation will help you:

  • Decide whether to store the data in a Postgres table hosted on Baseten or configure then connect your own data source,

  • Build and save SQL queries to surface the data in the front- and back-end of your applications, and

  • Read and write from data tables and data connections with Python from code files and the console.

Whether you're building a data labeling app, evaluating a model, or analyzing terabytes of media, review these docs to discover everything you need to store and use data.

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