Polars Raises $21M to Take on Apache Spark with Rust-Powered Data Platform

Amsterdam-based startup Polars, the company behind the popular open-source data tool of the same name, has secured $21 million (€18 million) in Series A funding led by Accel, with participation from Bain Capital Partners and angel investors.

What started as a pet project during COVID-19 by creator Ritchie Vink is now shaping the future of data processing. Frustrated with the limitations of Pandas, Vink built Polars in Rust, offering a faster and more efficient query engine. Polars has been downloaded over 24 million times by data scientists in fields like logistics, economics, and biology.

Why Investors Are Excited About Polars

While Polars gained attention for its performance and speed, this Series A round is about the company’s next growth phase. Two years after forming the company, Polars launched Polars Cloud, a managed data platform that allows users to run queries at scale.

The startup is also building Polars Distributed, a distributed engine designed to handle petabytes of data — a move that positions it as a challenger to Apache Spark and its commercial counterpart, Databricks.

Closing the Gap Between Pandas and Spark

For investors, the real value lies in Polars’ ability to close the scale gap. Pandas is widely used but limited to single-machine workloads, while Spark dominates large-scale distributed processing. Polars aims to bridge this divide, offering a single platform for datasets of any size and complexity.

Lessons for Open Source Founders

Accel partner Zhenya Loginov, who led the round, emphasized an important lesson. Open source projects become commercially viable when they solve outdated problems in large markets. Vink’s journey shows that turning a developer-focused tool into an enterprise solution can unlock significant opportunities.

With Polars Cloud and Polars Distributed, the company is entering a new chapter, one where it not only helps data scientists but also enterprises managing massive datasets.