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Cloudflare Basin represents a significant shift in the AI infrastructure landscape by offering a serverless, open-standard data platform built on Apache Iceberg and R2 storage. By eliminating data egress fees and enabling direct SQL querying of large datasets across regions, it lowers the cost and complexity of training and fine-tuning machine learning models at scale. This architecture allows developers to build portable data lakes that integrate seamlessly with various query engines, a critical requirement for modern AI development workflows.
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Introducing Cloudflare Basin: an open, serverless data platform, now generally available

Cloudflare Blog9 min de cititArticolul și perspectiva sunt în engleză.

Cloudflare Basin is built on Apache Iceberg and R2 Object Storage. With general availability, developers can ingest, manage, and query large datasets at scale without paying data egress fees.

During Birthday Week 2025, we announced the Cloudflare Data Platform, a suite of products that ingest, store, and query your analytical data. Today, we’re announcing that the platform is generally available, and we’re giving it a new name: Cloudflare Basin. Basin is a serverless data analytics platform built on Apache Iceberg, the open standard for data lakes, and R2 Object Storage. The Basin family includes: Basin Pipelines, formerly Cloudflare Pipelines, receives events from Workers, HTTP, or Cloudflare Logpush, transforms them with SQL, and writes them as Apache Iceberg tables or files in R2. Basin Catalog, formerly R2 Data Catalog, manages Iceberg metadata and automatically maintains tables to keep them fast and cost-efficient. Basin SQL, formerly R2 SQL, is our serverless, distributed SQL engine for querying Apache Iceberg tables directly on Cloudflare. Basin brings an end-to-end analytics platform to the Developer Platform, enabling you to collect data from a variety of sources, such as apps, infrastructure, devices, and other Cloudflare services, then query it to answer analytical questions. We set out to build a data platform last year when…

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