polars VS modin

Compare polars vs modin and see what are their differences.

polars

Dataframes powered by a multithreaded, vectorized query engine, written in Rust (by ritchie46)

modin

Modin: Scale your Pandas workflows by changing a single line of code (by modin-project)
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polars modin
144 11
25,298 9,408
5.7% 1.4%
10.0 9.6
5 days ago 7 days ago
Rust Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

polars

Posts with mentions or reviews of polars. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-08.

modin

Posts with mentions or reviews of modin. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-15.
  • The Distributed Tensor Algebra Compiler (2022)
    4 projects | news.ycombinator.com | 15 Jun 2023
  • A Polars exploration into Kedro
    6 projects | dev.to | 17 May 2023
    The interesting thing about Polars is that it does not try to be a drop-in replacement to pandas, like Dask, cuDF, or Modin, and instead has its own expressive API. Despite being a young project, it quickly got popular thanks to its easy installation process and its “lightning fast” performance.
  • Modern Polars: an extensive side-by-side comparison of Polars and Pandas
    5 projects | news.ycombinator.com | 7 Jan 2023
    Yeah, tried Polars a couple of times: the API seems worse than Pandas to me too. eg the decision only to support autoincrementing integer indexes seems like it would make debugging "hmmm, that answer is wrong, what exactly did I select?" bugs much more annoying. Polars docs write "blazingly fast" all over them but I doubt that is a compelling point for people using single-node dataframe libraries. It isn't for me.

    Modin (https://github.com/modin-project/modin) seems more promising at this point, particularly since a migration path for standing Pandas code is highly desirable.

  • Working with more than 10gb csv
    3 projects | /r/datascience | 5 Oct 2022
    Modin should fit. It implements Pandas APIs with e.g. Ray as backend. https://github.com/modin-project/modin
  • Modern Python Performance Considerations
    8 projects | news.ycombinator.com | 5 May 2022
  • How to Speed Up Pandas with 1 Line of Code
    2 projects | /r/Python | 3 Mar 2021
    The pandas library provides easy-to-use data structures like pandas DataFrames as well as tools for data analysis. One issue with pandas is that it can be slow with large amounts of data. It wasn’t designed for analyzing 100 GB or 1 TB datasets. Fortunately, there is the Modin library which has benefits like the ability to scale your pandas workflows by changing one line of code and integration with the Python ecosystem and Ray clusters
    2 projects | /r/Python | 3 Mar 2021

What are some alternatives?

When comparing polars and modin you can also consider the following projects:

vaex - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀

arrow-datafusion - Apache Arrow DataFusion SQL Query Engine

DataFrames.jl - In-memory tabular data in Julia

datatable - A Python package for manipulating 2-dimensional tabular data structures

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

db-benchmark - reproducible benchmark of database-like ops

rust-numpy - PyO3-based Rust bindings of the NumPy C-API

hdf5-rust - HDF5 for Rust

tidypolars - Tidy interface to polars

swifter - A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner

arrow2 - Transmute-free Rust library to work with the Arrow format

rust-csv - A CSV parser for Rust, with Serde support.