some sources:

- https://voltrondata.com/codex/a-new-frontier (links out to others) - https://wesmckinney.com/blog/looking-back-15-years/

in short you can think of a DB as at least 3 decoupled subsystems: UI, compute (query engine), storage. DuckDB has a query engine and storage format, and several UIs (SQL, Python, etc.). Trino is only a query engine (and UIs, everything has UIs). Polars has a query engine. DataFusion is a query engine (and other things). Spark is a query engine. pandas has a query engine

typically query engines are tightly coupled with the overall “product”, but increasingly compute, data (and even more recently via DuckLake metadata), and UI are decoupled allowing you to mix and match parts for a “decomposed database” architecture

quick disclaimer: I worked at Voltron Data but it’s a dead company walking, not trying to advertise for them by any means but the doc I linked is very well written with good information IMO