Polars, the Rust-based DataFrame library for data scientists and engineers, announced its seed funding of US$4 million led by Bain Capital Ventures 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 this 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.
“We 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. We gives those teams a high-performance library that handles much larger data sets, even on a single node. It is very easy to adopt for data practitioners who are already familiar with Pandas or R DataFrames.”
Founded by Polars creator and 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.”