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Polars Cloud GA: Bridging the DataFrame Scale Gap

2025-09-04

Polars Cloud is now generally available on AWS, along with the open beta launch of its novel distributed engine. This platform aims to bridge the gap between the ease of use of local pandas and the scalability of remote PySpark, offering a single API that seamlessly scales from laptop to cloud. Its distributed engine leverages Polars' innovative streaming architecture, enabling horizontal, vertical, and diagonal scaling strategies, significantly reducing cost, complexity, and improving performance. Future plans include on-premise support, a live cluster dashboard, task orchestration, autoscaling, catalog support, and multi-region deployment.

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Polars Cloud: A Scalable, Serverless DataFrame Processing Platform

2025-03-07

The Polars team is building Polars Cloud, a flexible DataFrame API platform backed by high-performance compute. It aims to bridge the gap between Pandas and PySpark, offering both ease of use and scalability. Polars Cloud supports distributed computing, serverless compute, configurable hardware (GPU and CPU), diagonal scaling (both horizontal and vertical), multi-cloud support (AWS, Azure, GCP), on-premise licensing, fault tolerance, data lineage, and observability. Users can execute queries remotely with simple API calls, supporting both batch and interactive modes. Polars Cloud also supports multiple scaling strategies, including distributed, partitioned, and parallel queries, to handle various data processing needs.

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