SedonaDB builds on libraries in the Rust ecosystem, like Apache DataFusion, to provide users with a nice geospatial DataFrame experience. It has functions like ST_Intersects that are common in spatial libraries, but not standard in most DataFrame implementations.

There are other good alternatives, such as GeoPandas and DuckDB Spatial. SedonaDB has Python/SQL APIs and is very fast. New features like full raster support and compatibility with lakehouse formats are coming soon!

Look, this article is absolutely excellent, and answers your questions. Please read the article before commenting this sort of thing.

As someone who has had to use geopandas a lot, having something which is up to an order of magnitude faster is a real dream come true.