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LanceDB supports Polars, a blazingly fast DataFrame library for Python written in Rust. Under the hood, both Lance and Polars speak Arrow, so passing data back and forth stays zero-copy and ergonomic.

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Create & Query a Table

Import the required libraries, including the optional Pydantic helpers if you plan to define schemas. Build a Polars DataFrame, convert it to Arrow, and use it directly when creating a LanceDB table. Run vector search and keep the results as a Polars DataFrame for further processing or visualization.

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Work with LazyFrames

When you want to operate on the entire table (potentially larger than RAM), convert to a Polars LazyFrame so you can chain transformations without loading everything at once.

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Define Schemas with Pydantic

You can also describe your table via LanceModel and continue ingesting data from Polars. This is useful when multiple teams share a schema or when you want validation.