Are they competing for something?

Actually yes. We had already been planning to do 2.0 for a long time. We originally said we'd move on from 1.x quickly when released 1.0 but ended up staying at 1.x much longer than intended.

From a quick check our first PRs were merged to the 2.0 branch in June:

    2026-06-17T21:27:51Z #27993 chore: Stop coercing `pl.col(...)` to selector ...
    2026-06-18T14:19:26Z #27996 chore!: Replace multi-seed hash API with a single seed
    2026-06-19T07:05:11Z #27991 chore(python!): Remove `Expr.flatten` function

I'm also using it for BlockRotate, it's time to upgrade.

my understanding is Polars is faster, scales better without using external solutions, better API, +Rust. Pandas wins if you want to use what the vast majority of folks are using and have used in the past. Probably has a more complete set of helpers / recipes for the little things you bump into when using it thoroughly, but in the age of LLMs, I think that's minor.

Polars is effectively a full replacement for Pandas for 99.9% of all cases. The only exception I'm really aware of is if you're working with geospatial data, as there isn't yet a "Geopolars" equivalent of the commonly used "Geopandas". However, Geopolars is still in active development and should eventually be production ready.