Lack of performance benchmark data hinders Haskell adoption in data tools
Problem
The blog claims that writing Parquet files with Haskell is fast, but commenters note that this claim lacks verifiable benchmark data and express interest in integrating Haskell with Apache Arrow, indicating a need for comparable performance data and broader ecosystem support.
Pain points
- Performance claims lack verifiable benchmark data
- Desire to integrate Haskell into the Apache Arrow ecosystem
Questions to verify
- Is there a team willing to provide benchmark data comparing Haskell with Pandas/Polars?
- Do you want native Haskell support in Apache Arrow?
- What are the current performance goals of the project?
Evidence
quote · @Anonymous
Looks like a pretty cool community building great tools with care. Using a functional language for data transforms sounds like a sane idea, haven't played around with it yet but it's definitely on my list now. However they claim using Haskell for data science is "fast", which doesn't really mean anything until you have numbers to show. A little benchmark with pandas and polars wouldn't hurt I guess.
quote · @Anonymous
I'd personally rather see Haskell become part of the options for https://arrow.apache.org/, but this is still a cool project.
Disclaimer: this card is distilled by AI from community discussions as “pain point evidence”. It is a starting point for need analysis and validation, not a “validated market need”. AI has analytical limits; please open the original discussion above to manually verify before key decisions.