neuronika VS polars

Compare neuronika vs polars and see what are their differences.


Tensors and dynamic neural networks in pure Rust. (by neuronika)


Fast multi-threaded DataFrame library in Rust and Python (by ritchie46)
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neuronika polars
10 33
568 3,122
8.1% 8.9%
6.8 9.9
6 days ago 6 days ago
Rust Rust
Mozilla Public License 2.0 MIT License
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.


Posts with mentions or reviews of neuronika. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-01.


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 2021-11-24.
  • Rust and what it needs to gain space in computation-oriented applications
    7 projects | | 24 Nov 2021
    You should check out polars, datafusion, influxdb iox and databend, all written in native Rust and powered by the Apache Arrow format. Polars in particular is pretty dam fast and has bindings for Python.
  • How to pass dataframes between Rust and Python?
    4 projects | | 20 Nov 2021
    A solution for either Polars or Datafusion (or something else?) would be fine. For both libraries, python packages exist, that contain the python bindings:
    4 projects | | 20 Nov 2021
    It's working for me now. :-) To get it working, I used the code from the suggested directory as well as the class PyPolarsError, which I copied into a local module: Besides the polars dependency, also these are needed:
    4 projects | | 20 Nov 2021
  • Introducing tidypolars - a Python data frame package with syntax familiar to R tidyverse users
    4 projects | | 10 Nov 2021
    The biggest difference with this one is that it's built on top of the polars package, which is probably the fastest data frame manipulation library out there. All of the other dplyr-to-python packages are build on top of pandas (which is very slow in comparison).
  • Introducing tidypolars - a Python data frame package for R tidyverse users
    9 projects | | 10 Nov 2021
    tidypolars uses the polars package as a backend, which might be the fastest data frame manipulation library out there. (Faster even than R's data.table, which has been the king of speed for many years.)
    9 projects | | 10 Nov 2021
  • Python and ETL
    3 projects | | 5 Nov 2021
    Shameless plug. But I genuinely believe polars is the best tool for the job if performance, schema validity and RAM usage is important to you. Dependent on your machine Its performance is 2x-70x times pandas. It uses arrow memory and thus has proper null handling, has query optimization, a lot of parallelization, insanely fast csv-parser and utilizes much less RAM then pandas.
  • Show HN: Dataframes in Elixir Backed by Rust
    6 projects | | 4 Nov 2021
  • Discussion: Integrating polars and plotters
    2 projects | | 26 Oct 2021
    For those who do not know about them, polars is a data frame crate for Rust and Python. It is also the fastest data frame library, according to benchmarks. Plotters is a crate for data visualisation. Both are the equivalents of pandas and matplotlib from the Python ecosystem. However, the integration with matplotlib in pandas has no equivalent. I would like to propose an effort to integrate polars with plotters, either by modifying the existing codebases, or creating a new bridge crate. I would love to hear opinions about this from the widder community.

What are some alternatives?

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

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

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

rust-ndarray - ndarray: an N-dimensional array with array views, multidimensional slicing, and efficient operations

arrow-rs - Official Rust implementation of Apache Arrow

wgpu - Safe and portable GPU abstraction in Rust, implementing WebGPU API.

db-benchmark - reproducible benchmark of database-like ops


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

rustdesk - Yet another remote desktop software

arrow2 - Unofficial transmute-free Rust library to work with the Arrow format

tokio-tungstenite - Tokio binding for Tungstenite, the Lightweight stream-based WebSocket implementation

are-we-learning-yet - How ready is Rust for Machine Learning?