alt Hacker NewsThis presentation does a good job distilling why FireDucks is so fast:
https://fireducks-dev.github.io/files/20241003_PyConZA.pdf
The main reasons are
* multithreading
* rewriting base pandas functions like dropna in c++
* in-built compiler to remove unused code
Pretty impressive especially given you import fireducks.pandas as pd instead of import pandas as pd, and you are good to go
However I think if you are using a pandas function that wasn't rewritten, you might not see the speedups
It’s not clear to me why this would be faster than polars, duckdb, vaex or clickhouse. They seem to be taking the same approach of multithreading, optimizing the plan, using arrow, optimizing the core functions like group by.