spark is certainly the incumbent for this sort of thing.

one benefit for me personally: you should be able to move from local dev to cloud more easily.

Yeah I reeeaaally want to see benchmarks! Single node duckdb is absolutely insane (as in fast) performance wise, especially compared to something like Spark. There's been a lot of speed focussed work in the project and I don't know of any faster data processing (I'm not counting traditional SQL since a lot of the speed benefits there come from indexing etc and essentially doing additional work ahead of time).

I guess it comes down to how well written the distributed workflows are, there's a lot to get wrong, but in theory it should be able to achieve very impressive numbers.

My reasoning behind this is Dask, which uses Pandas under the hood being capable of better benchmarks than Spark, I think this is partly some good optimisations, but also simply that pandas is faster than spark's row based model. Duckdb is on some benchmarks more than 10x faster than pandas, you can see where this is going. . .