TL;DR
- Cloudflare Basin, the rebranded Data Platform, is now generally available as an end-to-end serverless analytics suite with three core products: Pipelines, Catalog, and SQL
- Basin is built on Apache Iceberg and R2 Object Storage, enabling data portability across query engines and zero egress costs for accessing data
- The platform supports real-time data ingestion at up to 3GB/s per stream, automatic table maintenance, and distributed SQL queries across Cloudflare's global network
- Pricing is usage-based with no hourly charges or infrastructure costs, making it practical for hobby projects through enterprise-scale analytics workloads
- Status
- Generally available
- Core products
- Pipelines, Catalog, SQL
- Built on
- Apache Iceberg and R2
What happened
Cloudflare announced that its Data Platform, which launched during Birthday Week 2025, is now generally available. The company has also renamed the platform to Cloudflare Basin to better reflect its unified architecture and ambitions. Basin is a serverless data analytics platform built on Apache Iceberg, the open standard for data lakes, and Cloudflare's R2 Object Storage.
The three products
Basin consists of three integrated products. Basin Pipelines receives events from Workers, HTTP endpoints, or Cloudflare Logpush, transforms them using SQL queries, and writes the results as Apache Iceberg tables or files to R2. The Pipelines now support ingestion at up to 3GB/s per stream and include features such as Cloudflare Logpush integration, schema-aware Worker bindings that generate TypeScript types, and data quality error visibility through the dashboard and GraphQL API. Basin Catalog manages Apache Iceberg metadata and automatically maintains tables to ensure performance and cost efficiency. It offers per-table compaction policies, automatic snapshot expiration, unreferenced data-file cleanup, and manifest optimization. Basin SQL is a serverless, distributed query engine for querying Apache Iceberg tables directly on Cloudflare. It supports standard SQL operations including joins, aggregations, window functions, and over 190 scalar and aggregate functions for strings, timestamps, regular expressions, cryptography, statistics, arrays, maps, and structs.
npx wrangler basin catalog create CATALOG_NAMEArchitecture and design principles
Basin is built around three core principles: speed, openness, and cost efficiency. The platform enables developers to create a catalog, set up data ingestion, and query results within seconds. As datasets grow, Basin Catalog compacts metadata and generates statistics for query planning, while Basin SQL distributes queries across Workers to maintain consistent performance. The emphasis on openness stems from the growth of the Apache Iceberg ecosystem. Developers can read and write data using any Iceberg-compatible engine, including PyIceberg, DuckDB, Snowflake, and Apache Spark. This portability is enabled by Cloudflare's zero egress fees, allowing developers to access their data from various tools regardless of region or cloud provider. Cost efficiency is achieved through usage-based pricing with no hourly charges or separate infrastructure costs. Developers are only billed when Basin ingests, processes, or queries their data, making it practical for hobby projects while scaling economically for enterprise use cases.
What changed since beta
Since launching in open beta, Basin has undergone significant improvements. Basin Pipelines now supports the Cloudflare Logpush integration for transforming logs into compressed Parquet files or Iceberg tables, and includes schema-aware Worker bindings that generate TypeScript types. Data quality errors are now visible through the dashboard and GraphQL API, distinguishing between dropped events, missing fields, type mismatches, parse failures, and null values. The entire ingestion path can be managed as infrastructure as code using Terraform resources. Basin Catalog has evolved to include per-table compaction policies based on access patterns, automatic snapshot expiration with retention policies, unreferenced data-file cleanup without requiring separate Spark jobs, and manifest optimization to reduce metadata I/O. Basin SQL has expanded from basic filtering and exploration to support hundreds of functions, including standard and approximate aggregations, complex joins, window functions, and a suite of JSON functions.
WITH account_activity AS (
SELECT
a.plan,
e.account_id,
count(*) AS events,
approx_distinct(e.user_id) AS active_users
FROM analytics.events e
JOIN analytics.accounts a
ON e.account_id = a.account_id
WHERE e.event_time >= '2026-09-01T00:00:00Z'
GROUP BY a.plan, e.account_id
)
SELECT
*,
rank() OVER (PARTITION BY plan ORDER BY events DESC) AS activity_rank
FROM account_activity
QUALIFY rank() OVER (PARTITION BY plan ORDER BY events DESC) <= 10;Planned improvements
Cloudflare has outlined several features currently in development. Basin Pipelines will add custom partitioning when writing to Basin Catalog, schema migrations, updatable configuration and Pipeline SQL, support for Iceberg V3 including the Variant type for semi-structured data, and stateful processing for streaming aggregations, joins, and incrementally updated materialized views. Basin Catalog will introduce a new compaction approach to efficiently sort and cluster data for improved query performance, more granular authentication controls for namespaces and tables, and jurisdiction support for data sovereignty and compliance requirements. Basin SQL is working on advanced statistics and adaptive scheduling to improve performance and efficiency, full data definition language support directly from SQL, Iceberg V3 support including Variant and geospatial types, and continued expansion of SQL compatibility and observability.
Getting started
Basin Pipelines, Basin Catalog, and Basin SQL are now generally available and can be used together as an end-to-end platform or individually within existing architectures. Developers can follow the getting started tutorial to begin ingesting events and querying their data.
Source
Cloudflare Bloghttps://blog.cloudflare.com/cloudflare-basin/AI-assisted, verified against the source. This post was drafted with AI from the primary source linked above and checked automatically against it. For anything you depend on, read the original.
- #analytics
- #dataplatform
- #apacheiceberg
- #serverless
- #r2
