Polars, a DataFrame library based on the Rust programming language for data scientists and engineers, announced its seed funding of €3.6 million led by Bain Capital Ventures (BCV) with participation from individual investors. The funding will be used to expand the team, and build a compute platform to efficiently run Polars at any scale.
Founder Ritchie Vink started the Polars project with the goal of bringing high-performance scientific and numeric data processing to the laptop. Polars empowers data scientists and engineers to analyze large DataFrames without having to set up and maintain a distributed compute cluster. Today, Polars is one of the fastest DataFrame libraries in existence, and one of the fastest-growing data processing projects on GitHub.
“Polars will let data scientists and engineers focus more on their code and less on infrastructure,” said Slater Stich, Partner at BCV. “Historically, data teams have faced a big leap in infrastructure complexity once the DataFrames they’re working with grow beyond a few gigabytes in size. Polars gives those teams a high-performance library that handles much larger data sets, even on a single node. Polars is easy to adopt for data practitioners who are already familiar with Pandas or R DataFrames.”
Founded in 2020 by machine learning engineer, Ritchie Vink, and his co-founder Chiel Peters, former CTO at Xomnia, the company will be built around the open-source Polars project, and will focus on furthering Polars’ scalability and interoperability in enterprise environments.
“What started as a pet project of mine in 2020 has grown beyond my expectations, thanks to the open source community,” said Vink. “Now, with the support of our investors and our community, we will focus on offering managed environments, improving cloud connectors, and supporting the many companies that already use Polars.”
The Polars OSS is MIT-licensed, and the company will continue to sponsor and accelerate the open-source development of Polars.