I don’t use Polars directly, but instead I use it as a materialization format in my DuckDB workflows.

Duckdb.query(sql).pl() is much faster than duckdb.query(sql).df(). It’s zero copy to Polars and happens instantaneously while Pandas takes quite a while if the DataFrame is big. And you can manipulate it like a Pandas DataFrame (albeit with slightly different syntax).

It’s greater for working with big datasets.