For anyone who doesn't use those libraries, they are all targeted towards out-of-core data processing (i.e. computing across multiple machines because your data is too big). Comparing them to a single core data frame library is just silly, and they will obviously be slower because they necessarily come with a lot of overhead. It just wouldn't make sense to use polars in the same context as those libraries, so seeing them presented in benchmarks as if they are equivalents is a little silly.
And on top of that, duckdb, which you might use in the same context as polars and is faster than polars in a lot of contexts, isn't included in the benchmarks.
The software engineering behind polars is amazing work and there's no need to have misleading benchmarks like this.