I showed Julia is much faster than Python in data processing.

This page summarizes the projects mentioned and recommended in the original post on reddit.com/r/Julia

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  • polars

    Fast multi-threaded DataFrame library in Rust | Python | Node.js

    I think that the best part of the Julia performance is that it is achieved with pure Julia libraries. I think some of these performance gaps are going to close once all of the Python and R packages complete their transition to Arrow. I'd be curious to see how the Polars library did on this task, for instance.

  • Apache Arrow

    Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing

    I think that the best part of the Julia performance is that it is achieved with pure Julia libraries. I think some of these performance gaps are going to close once all of the Python and R packages complete their transition to Arrow. I'd be curious to see how the Polars library did on this task, for instance.

  • Scout APM

    Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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