Our Blog

Polars is 3x faster than Spark and more than 6x faster on a single node, on the PDS-H benchmark.

Tue, 16 Jun 2026

Launching Polars Distributed on Kubernetes

by Chiel Peters

We are launching our distributed engine on Kubernetes (e.g. on-prem, AKS & GKE). Try it for free. It also ships with advanced query profiling and OpenLineage support.

Wed, 3 Jun 2026

Announcing Polars 1.41

by Thijs Nieuwdorp

Polars 1.41 brings a hand-written Thrift decoder for faster Parquet metadata reads, nested common subplan elimination in the optimizer, and LazyFrame.gather.

Tue, 26 May 2026

Handling Schema Issues in Polars

by Thijs Nieuwdorp

How Polars handles schema mismatches across CSV schema inference, multi-file Parquet datasets, Delta Lake writes, Apache Iceberg, and when you need to take control manually.

Thu, 30 Apr 2026

Polars in Aggregate: Streaming Expands, Lakehouse I/O, and Cloud Profiling

by Thijs Nieuwdorp

This edition covers the streaming engine's expansion across sinks and joins, new Iceberg and Delta I/O, Polars Cloud query profiling, and the new PartitionBy API.

Thu, 16 Apr 2026

Streaming sort-merge joins in Polars

by Thijs Nieuwdorp

Learn how Polars streaming sort-merge join works, the concepts behind the algorithm, and how you can verify the query planner chose the merge-join.

Thu, 9 Apr 2026

Introducing the Query Profiler and Optimizing Cluster Configuration

by Thijs Nieuwdorp

Introducing the Polars Cloud query profiler. In this post we use it to identify performance bottlenecks and select the right instance family, instance type, and cluster size for your workload.

Thu, 26 Mar 2026

Orchestrating Polars Cloud Queries with Apache Airflow

by Thijs Nieuwdorp

How to schedule and run Polars Cloud queries using Airflow, covering fire-and-forget jobs, parallel execution, multi-stage pipelines, and cluster management.

Tue, 17 Feb 2026

Understanding the New Categorical

by Thijs Nieuwdorp

Exploring the evolution of the Categorical data type in Polars.

Thu, 29 Jan 2026

How Rabobank leverages window functions to drastically improve performance

by Freerk Venhuizen, Senior Data Scientist @ Rabobank

Window functions are a perfect fit for detecting periodic payment bookings at Rabobank. They not only improve performance but also makes code easier to read.

Wed, 10 Dec 2025

Polars in Aggregate: Polars Cloud, Streaming engine, and New Data Types

by Thijs Nieuwdorp

This edition covers the launch of Polars Cloud, the new streaming engine, the Categoricals overhaul, the stabilization of Decimals, introduction of Int128, and the introduction of runtimes.

Wed, 3 Dec 2025

Supercharging Analytics with Polars: A Case Study in Analyst Empowerment

by Tyler Riccio, Assistant Vice President Enterprise Data and Analytics @ Citizens

With Polars, Citizens achieved faster development cycles, richer and more timely insights, and created a strong pillar for the ongoing modernization journey.

Wed, 26 Nov 2025

Polars helps coping with black swan events at La Mobilière

by Dr. Michael Tomka - Actuary @ La Mobilière and Dr. Santiago Padrón - Senior Data and Machine Learning Consultant @ D ONE

La Mobilière always keeps its promise. Now, even more promptly, thanks to Polars.

Thu, 9 Oct 2025

Polars raises €18M Series A to build fast, ergonomic data processing at any scale

by Ritchie Vink

We have raised €18M in Series A funding the build the next generation data.

Mon, 29 Sept 2025

Polars at Decathlon: Ready to Play?

by Arnaud Vennin (Tech Lead Data Engineer @ Decathlon)

Decathlon adopts Polars to replace increasing number of workloads on Spark to significantly decrease infrastructure cost and complexity.

Mon, 15 Sept 2025

Launch of Polars Cloud and Distributed Polars

by Ritchie Vink

We launch Polars Cloud; the distributed Cloud Architecture to run Polars anywhere

Wed, 3 Sept 2025

Polars Meetup #2: Polars at Scale

by Ritchie Vink

Ritchie Vink introduces Polars Cloud, the platform to scale Polars remotely with a novel distributed engine

Thu, 31 Jul 2025

Introducing UVM for larger than VRAM data on the Polars GPU engine

by Thijs Nieuwdorp (Xomnia), Tom Drabas (NVIDIA)

With the introduction Unified Virtual Memory (UVM), larger than memory data processesing is possible with the GPU engine. Learn more about the implementation and performance considerations.

Thu, 26 Jun 2025

Updated PDS-H benchmark results (May 2025)

by Ritchie Vink

A fresh run of the PDS-H benchmark suite shows the performance of Polars versus other query processing engines.

Sun, 1 Jun 2025

METRO.digital Optimized Their KPI Creation Process Across 19 Countries with Polars

by Dr. Patrick Bormann (Tech lead data scientist) @ METRO.digital

METRO.digital migrated from SQL to Polars for KPI creation across 19 countries, improving code maintainability and reducing resource requirements while handling large datasets more efficiently.

Thu, 24 Apr 2025

Polars Meetup #1: New Streaming Engine

by Orson Peters

Orson Peters walks through the core architecture and internals of the new Polars streaming engine

Wed, 9 Apr 2025

Polars Cloud; the distributed Cloud Architecture to run Polars anywhere

by Ritchie Vink

We introduce Polars Cloud, the distributed cloud architecture to scale and run Polars anywhere.

Mon, 10 Feb 2025

Exploring calendar-aware date operations in Polars

by Rodrigo Girão Serrão

Explore the calendar-aware date operations that Polars supports to simplify working with dates.

Mon, 23 Dec 2024

Breaking the rules with expression expansion

by Rodrigo Girão Serrão

Polars has a rule that one expression must produce a single column as a result in a query. How do some expressions break this rule?

Thu, 5 Dec 2024

Polars in Aggregate: Faster I/O, inequality joins, and much more

by Rodrigo Girão Serrão

This edition covers plenty of performance improvements made to I/O, inequality joins, and much more.

Wed, 4 Dec 2024

Understanding Polars data types

by Rodrigo Girão Serrão

Learn about all Polars data types, including when to use them and how to use them.

Tue, 26 Nov 2024

PyData NYC 2024: Polars GPU Acceleration

by Ritchie Vink

Ritchie Vink presents Polars GPU acceleration at PyData NYC 2024

Mon, 25 Nov 2024

PyData Amsterdam 2024: Polars 1.0 and Beyond

by Ritchie Vink

Ritchie Vink presents Polars 1.0 and the arrival of GPU acceleration at PyData Amsterdam 2024

Tue, 22 Oct 2024

Efficient Cloud Data Processing with Polars – a DB Systel Case Study

by Sebastian Folz, Maren Westermann (Machine Learning Engineers @ DB Systel GmbH)

The largest german railway company achieves nearly 20x speedup in data processing and identifies significant potential for cost savings on cloud resources.

Thu, 17 Oct 2024

Joulen accelerates the transition to sustainable energy practices using Polars

by Liam Brannigan (Data Team Lead) @ Joulen

Joulen builds a highly scalable and cost-effective infrastructure with Polars to power tools to optimize the use of renewable assets.

Wed, 25 Sept 2024

GPU acceleration with Polars and NVIDIA RAPIDS

by Ritchie Vink, Robin van den Brink, Lawrence Mitchell

Polars and NVIDIA RAPIDS have worked together to bring GPU acceleration to Polars.

Tue, 17 Sept 2024

Transforming Music Data Management: How Polars Redefined CSV Processing at Vydia

by Danny Correia (Software Engineering Manager) @ Vydia

Vydia uses Polars' Ruby interface to ingest and process a fast growing number of CSVs files on their Ruby based platform that empowers music labels.

Fri, 13 Sept 2024

Polars has a new lightweight plotting backend

by Marco Gorelli (Polars core developer)

With Polars 1.6 a new lightweight plotting engine was introduced to create plots without additional dependencies.

Wed, 4 Sept 2024

Benchmarking energy usage and performance of Polars and pandas

by Ivano Malavolta and Karolina Bargieł

A research team of the VU Amsterdam published a paper benchmarking the energy usage and performance of pandas and Polars data analysis Python libraries.

Thu, 22 Aug 2024

Complex Calculations vs. Polars Plugins - A Double River Case Study

by Isaac Robbins (Data Engineer) & Nelson Griffiths (Engineering & ML Lead) @ Double River Investments

Double River achieves 10x speedups and 50% memory reduction in their financial models utilizing Polars plugins.

Wed, 14 Aug 2024

Hugging Face x Polars

by Polars Development Team

Polars now supports native reading from Hugging face datasets

Fri, 9 Aug 2024

Polars in Aggregate: Improved I/O, Hugging Face support, and more

by Polars dev team

This edition covers improved support for Hive partitioning, right joins, Hugging Face integration and much more.

Thu, 25 Jul 2024

Announcing Polars 1.0

by Ritchie Vink

We have released Python Polars 1.0. We are very excited to reach this milestone.

Mon, 1 Jul 2024

Processing hundreds of GBs of textual data on a daily basis at MDPI

by Jean-Philippe Dubuc, Senior Data Engineer @ MDPI

MDPI, a pioneer in open access scientific publishing, uses Polars to process hundreds of GBs of textual data on their on-premise infrastructure on a daily basis.

Thu, 27 Jun 2024

Polars in Aggregate: Faster CSV writer, dead expression elimination, and more

by Robin van den Brink & Ritchie Vink

This Polars in Aggregate shares more insights in some selected changes released in the versions Polars 0.20.17 to Polars 0.20.31.

Wed, 5 Jun 2024

PyCon Lithuania 2024: Keynote on Polars

by Ritchie Vink

Ritchie Vink delivers a keynote on Polars at PyCon Lithuania 2024

Thu, 2 May 2024

G-Research tackles the biggest financial data challenges of tomorrow with Polars

by Kieran Garvey (Senior L&D Partner) & Casey Haaland (Machine Learning Engineer) @ G-Research

G-Research is a leading quantitative finance research firm that uses Polars in different projects throughout the organization.

Thu, 18 Apr 2024

Updated PDS-H benchmark results

by Stijn de Gooijer

A fresh run of the PDS-H benchmark suite shows the performance of Polars versus other query processing engines.

Tue, 16 Apr 2024

Accelerating Polars DataFrames

by Polars & NVIDIA

Polars and NVIDIA are bringing GPU acceleration to Polars dataframes in the near future. With the collaboration Polars is able to fully utilize both the CPU and GPU, significantly speeding up certain workloads.

Thu, 4 Apr 2024

Polars in Aggregate: New integrations, enhanced NumPy interop, and improved performance

by Polars dev team

This edition covers support for streaming outer joins, zero-copy NumPy interop, COUNT(*) fast path, very fast boolean filters and ternary operations, and more.

Thu, 28 Mar 2024

The power of predicate pushdown

by Chiel Peters

Predicate pushdown is one of the most important optimizations for a query engine. Read more about it in this article.

Tue, 19 Mar 2024

Check Technologies saves 25% of cloud expenses with Polars

by Robin van den Brink, Paul Duvenage (Check Technologies)

Check Technologies is a Dutch multi-modal mobility provider in the Netherlands. They have successfully migrated all data pipelines from pandas to Polars and saved 25% on their cloud bills.

Wed, 6 Mar 2024

Polars in Aggregate: New string type, plotting, SQL and more

by Robin van den Brink, Ritchie Vink