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§ Private Profile · Amsterdam, Noord-Holland, The Netherlands
Polars is a technology company.
Polars offers an open-source, high-performance DataFrame library for rapid data manipulation on a single machine. Its multi-threaded query engine, built in Rust, leverages parallelism, vectorized processing, and a columnar memory layout for superior performance. Polars integrates the Apache Arrow memory model for efficient data sharing, providing a structured, expressive API.
Ritchie Vink created Polars, driven by a need for exceptional speed and efficiency in data processing beyond existing frameworks. His insight focused on optimizing modern hardware from inception. Chiel Peters later co-founded the formal company, strategically expanding the project's development and community reach.
Polars serves data professionals and developers needing fast, efficient processing for large datasets. Its design enables optimized queries, with the engine intelligently executing for maximum hardware utilization. The company's vision is to provide a robust, open-source foundation that simplifies tasks and fosters a high-performance, collaborative community.
Polars has raised $25.0M across 2 funding rounds.
Polars has raised $25.0M in total across 2 funding rounds.
Polars has raised $25.0M in total across 2 funding rounds.
Polars's investors include Accel, C2 Investment, Khosla Ventures, Pareto Holdings, Akshay Kothari, Dharmesh Shah, Elad Gil, Bain Capital, Slater Stich.
Polars has raised $25.0M across 2 funding rounds. Most recently, it raised $21.0M Series A in September 2025.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Sep 1, 2025 | $21M Series A | Accel | C2 Investment, Khosla Ventures, Pareto Holdings, Akshay Kothari, Dharmesh Shah, Elad GIL, Bain Capital | Announced |
| Aug 3, 2023 | $4M Seed | Slater Stich | — | Announced |
Polars is a technology company built around an open-source data manipulation library of the same name, designed to provide a high-performance, scalable DataFrame solution. The core product is a Rust-based OLAP (Online Analytical Processing) query engine that supports multiple programming languages including Python, Rust, Node.js, and R. Polars serves data scientists, analysts, and engineering teams across sectors such as finance, life sciences, and logistics by enabling faster and more efficient data processing compared to traditional tools like pandas. The company has expanded its offerings with Polars Cloud, a managed data platform for scalable cloud queries, and Polars Distributed, a distributed engine targeting petabyte-scale data workloads, positioning itself as a challenger to Apache Spark[1][3][5].
Polars originated in 2020 as a pet project by Ritchie Vink, who was frustrated with the limitations of pandas during the COVID-19 pandemic. Vink, together with co-founder Chiel Peters—former CTO of Xomnia—leveraged their data platform experience to build a Rust-based query engine that could handle data more efficiently. The open-source project quickly gained traction, amassing over 19,000 GitHub stars and millions of downloads within a few years. The company was formally established to commercialize and scale the technology, raising a $4 million seed round in 2023 and a $21 million Series A in 2025 led by Accel and Bain Capital Ventures. Early pivotal moments include the launch of Polars Cloud and the public beta of Polars Distributed, marking a shift from open-source tool to enterprise-grade platform[1][2][3][4].
Polars rides the trend of increasing demand for efficient, scalable data processing tools as data volumes grow exponentially. The timing is critical as legacy tools like pandas struggle with performance and scalability, and distributed engines like Apache Spark face complexity and cost challenges. Polars leverages modern systems programming (Rust) and columnar memory formats (Apache Arrow) to deliver high performance on commodity hardware and cloud environments. By offering a simpler, faster alternative that scales from laptops to petabyte-scale clusters, Polars influences the data ecosystem by pushing for more accessible, energy-efficient, and performant data analytics tools[1][2][3][5].
Polars is poised to expand its influence by continuing to develop its distributed computing capabilities and managed cloud services, aiming to capture market share from incumbents like pandas and Apache Spark. Future trends shaping its journey include the growing emphasis on energy-efficient computing, the rise of cloud-native data platforms, and the increasing need for real-time, large-scale data processing. As Polars matures, it may become a foundational technology in data science and engineering workflows, driving innovation in how organizations handle big data. Its open-source roots combined with enterprise-grade offerings position it well for sustained growth and ecosystem impact[1][2][3].