Both are columnar (disk-)storage formats for use in data analysis systems. Both are integrated within Apache Arrow (pyarrow package for python) and are designed to correspond with Arrow as a columnar in-memory analytics layer.

How do both formats differ?

Should you always prefer feather when working with pandas when possible?

What are the use cases where feather is more suitable than parquet and the other way round?

Appendix

I found some hints here https://github.com/wesm/feather/issues/188, but given the young age of this project, it's possibly a bit out of date.

Not a serious speed test because I'm just dumping and loading a whole Dataframe but to give you some impression if you never heard of the formats before: