News
Nov 11, 2025
Startups
Data
Europe
NewDecoded
3 min read
Polars, the fast-growing open-source data processing engine built in Rust, has raised €18 million in Series A funding led by Accel with participation from Bain Capital Ventures. The Amsterdam-based company, founded in 2020 by Ritchie Vink and Chiel Peters, has become one of the fastest-growing data infrastructure projects on GitHub. The investment follows a $4 million seed round in 2023 that helped propel the platform's rapid adoption.
Since its seed investment, Polars has grown from 250,000 to over 23 million monthly users, with total downloads exceeding 250 million. The platform has attracted enterprise adoption from companies including Netflix, Microsoft, and G-Research. Built using Apache Arrow Columnar Format, Polars delivers exceptional performance that users consistently describe as orders of magnitude faster than traditional frameworks like pandas.
The Series A funding will support three key initiatives: making Polars OSS fully streaming to maximize single-node hardware utilization, developing a state-of-the-art distributed engine for cloud and on-premises deployment, and expanding Polars Cloud with managed infrastructure and autoscaling capabilities. The company's vision centers on providing one intuitive DataFrame API that works optimally across all scales. Users can transition from local to distributed execution with a simple .remote() call, eliminating the need to rewrite code as data volumes grow.
Polars Cloud, currently live on AWS, reflects the company's belief that developers shouldn't need different tools like PySpark depending on scale. The platform aims to deliver the best single-node performance while seamlessly scaling to distributed environments when needed. This approach challenges the fragmented landscape of data processing tools that force developers to learn multiple frameworks.
Despite commercial ambitions, Polars remains committed to its open-source roots under the MIT license. Founder Ritchie Vink emphasizes that improvements to the commercial distributed offering directly strengthen the OSS project, as the company leverages the open-source streaming engine on worker nodes. The company views this symbiotic relationship as fundamental to its long-term strategy, ensuring the community and enterprise customers both benefit from continuous innovation.
Polars' Series A signals a broader shift in data infrastructure toward Rust-based, columnar processing engines that challenge Python-era incumbents. The timing is notable as organizations increasingly struggle with pandas' limitations and PySpark's complexity, creating demand for modern alternatives that combine single-node performance with distributed scalability.
Accel's investment validates that the data processing market is ripe for disruption, particularly as the gap widens between what legacy frameworks can deliver and what modern data workloads require. By maintaining open-source principles while building commercial cloud offerings, Polars follows a proven infrastructure software playbook that benefits both community adoption and enterprise monetization.
The company's emphasis on a unified API across scales addresses a persistent pain point where data teams maintain separate codebases for different processing tiers, suggesting Polars could fundamentally simplify data engineering workflows.