Polars
An open-source, high-performance DataFrame library for Rust and Python, designed for efficient data manipulation and analysis.
About
Polars is an open-source library for data manipulation, recognized as one of the fastest single-machine data processing solutions. It offers a well-structured, typed API for expressive and easy-to-use data wrangling, built with performance in mind through its multi-threaded Rust query engine. Polars also provides Polars Cloud for scaling data queries from laptops to production workloads, deployable in the cloud or on-premise. Teams look it up for Data Manipulation, Data Analysis, DataFrame Library.
Frequently asked
What does Polars do?
Polars is a Data Manipulation company that offers Software. Teams look it up for Data Analysis, DataFrame Library, Open Source. Public records show about 26 people and $21M raised. Compare it on funding, headcount, reviews and nearby alternatives rather than the marketing line alone.
How much funding has Polars raised?
Polars has raised a total of $21M in funding. The most recent round on record is Series A.
What industry does Polars operate in?
Polars operates in Data Manipulation, Data Analysis, DataFrame Library, Open Source, Python Library.
How many employees does Polars have?
Polars has approximately 26 people on record.
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“In python notebooks 3.11 kernel, this works: pl.read_delta(table_path) Now failing in 3.12 with: DefaultAzureCredential failed to retrieve a token from the included credentials.”
View on Reddit“A while ago I switched from pandas to polars for data processing because coworkers insisted it's the new standard and much faster. I've found it fairly smooth to work with so far but there's one thing I'm running into which is that polars,…”
View on Reddit“Polars vs pandas. I am trying to come from database development into python ecosystem. Wondering if going into polars framework, instead of pandas will be any beneficial?”
View on Reddit“Hi, I decided to test DuckDB and Polars in a pure Python notebook, as I don't have experience with these python dialects. Here's what I did: Loaded Contoso 100 k, 10 m and 100 m datasets from CSV files into a Fabric SQL Database.”
View on Reddit“I've always struggled with when to use Spark versus tools like Polars or DuckD”
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