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Same. Almost every time I would use its streaming interfaces in Python, it would STILL materialize everything into memory. That was like 6 months ago. Maybe streaming interfaces actually work, but I found them to be leaky abstractions that required a ton of hand holding to make sure they didn't build a bunch of memory pressure, if you're lucky enough to even have a way to do it.

For example, last time I used it, you couldn't do NDJSON streaming scans from S3 (looks like fixed with PR #26563).

SQL is a terrible api for data transformation.

https://duckdb.org/docs/lts/sql/statements/pivot#limitations

vs

https://docs.pola.rs/api/python/stable/reference/dataframe/a...

even for just in-memory quick data analysis?

spinning up a venv with duckdb: 5 minutes

using sql everywhere; never having to remember dataframe syntax: timeless

what is the visualisation strategy here? I find post-hoc grouping and plotting in pandas pretty satisfying.

Check out malloyyo on github

Yep, and chdb as well. Said this before, chdb's DatStore is a pretty neat pandas replacement too.