The archive · Developer & Business Tools · Strategic decision · 2020–2025
Polars bets one DataFrame API spans pandas to Spark; €18M Series A from Accel
Amsterdam's open-source Rust dataframe Polars hit 25M downloads/month; the company behind it raised €18M Series A to launch Polars Cloud.
Polars
What the business is
Amsterdam startup behind the open-source Rust DataFrame library Polars; it sells Polars Cloud (managed, AWS-hosted) and Polars Distributed (on-prem) for data processing at any scale.
Starting capital：$4M seed led by Bain Capital (2023); €18M (~$21M) Series A led by Accel with BCV follow-on, Sept 2025
How it started
Ritchie Vink started Polars in 2020 as a COVID-era pet project, frustrated that pandas could not scale efficiently as data volumes grew, and wrote a faster DataFrame query engine in Rust. With co-founder Chiel Peters (former Xomnia CTO), the project became a company in 2023, raising a $4M seed led by Bain Capital.
What happened
Adoption grew from 250k to 23M+ monthly users within two years of the seed. In September 2025 the company closed an €18M Series A led by Accel, launched Polars Cloud on AWS, and put Polars Distributed — a distributed engine aimed at petabyte-scale workloads — into public beta, explicitly positioning against Apache Spark.
How it ended up
Still running and scaling: Series A closed 2025-09-29, Polars Cloud live on AWS, Polars Distributed in public beta, hiring Rust engineers for the distributed engine; no exit.
Background
Polars is an Amsterdam startup behind the open-source Rust DataFrame library of the same name, started in 2020 by Ritchie Vink as a COVID-era side project. Frustrated that pandas could not scale efficiently as data volumes ballooned, Vink wrote a faster query engine from scratch in Rust, with tight integration from I/O to execution.
The bet was that one DataFrame API could close the 'scaling gap': pandas is limited to a single machine, while Apache Spark needs a cluster even for small work. With co-founder Chiel Peters, Polars became a company in 2023, raised a $4M seed led by Bain Capital, and watched adoption grow from 250k to over 23M monthly users within two years.
In September 2025 the company closed an €18M (~$21M) Series A led by Accel with BCV following on, launched Polars Cloud on AWS, and put Polars Distributed into public beta to take on petabyte-scale workloads and challenge Spark. Silicon Canals reported 33k+ GitHub stars, 25M downloads a month and 250M+ total downloads by October 2025.
Polars stays committed to OSS — the same streaming engine that powers the free library runs on the cloud product's worker nodes — while building a managed platform with autoscaling, query insights and on-prem deployment, targeting the Python data ecosystem as the default choice for tabular data.
What has to be true
- Pandas' single-node ceiling was a real, widely felt pain: Polars proved speed and memory efficiency on a laptop before any commercial pitch existed.
- The Rust rewrite gave a durable performance edge — full control over I/O and query execution layers — that a fork of pandas could not match.
- The scaling-gap positioning created two markets at once: OSS adoption built a huge community, and Polars Cloud/Distributed gave enterprises a paid path without rewriting pipelines.
- Backing from Bain Capital in 2023 and Accel in 2025 validated the OSS-to-cloud playbook at a moment when data teams were actively seeking pandas alternatives.
What can be applied
Win on raw performance first, monetize the gap incumbents leave: Polars beat pandas on speed for free, then charged enterprises for a single API that scales from laptop to cluster.
Aftermath
As of 2026-09-02, Polars is live and scaling: €18M in new capital from Accel-led Series A (Sept 2025), Polars Cloud running on AWS, and Polars Distributed in public beta with an on-prem roadmap for data-sovereignty customers. The company reports 25M+ downloads per month and 33k+ GitHub stars as of October 2025 and continues hiring Rust engineers for its distributed engine, with the stated goal of becoming the default DataFrame tool from laptop to petabyte-scale clusters.
Sources
- The startup behind open source tool Polars raises $21M from Accel
- Polars raises €18M Series A to build fast, ergonomic data processing at any scale
- From laptop to cluster: Polars is closing the data scaling gap with a unified DataFrame API
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