The Apache Hudi team is pleased to announce the release of Apache Hudi
1.2.0.

Apache Hudi is an open data lakehouse platform, built on a high-performance
open table format to ingest, index, store, serve, transform, and manage
your data across multiple cloud data environments.

This 1.2.0 release comes 5 months after 1.1.1. It includes more than 600
commits from our incredible community. The 1.2.0 release expands the
lakehouse for multimodal and AI workloads while continuing to strengthen
its streaming and operational foundations:

   - Native VECTOR Type and Vector Search: First-class support for
   embeddings with built-in similarity search directly on Hudi tables.
   - Native BLOB and VARIANT Support: Store binary objects, documents,
   images, and semi-structured data alongside traditional analytical records.
   - Lance File Format Integration: Optimized storage for vector and
   multimodal data, for AI workloads within the Hudi ecosystem.
   - Major Flink Performance Boosts: Record Level Index support, dynamic
   bucket scaling, and a new FLIP-27 based source for large-scale streaming
   workloads.
   - Distributed Co-ordination at Scale: Expanded multi-writer concurrency
   control, automated table services, and operational improvements across the
   platform.

Please read the announcement blog and review the release notes for details
on release highlights and behavior changes before adopting the 1.2.0
version:
https://hudi.apache.org/blog/2026/06/07/apache-hudi-release-1-2-announcement/
https://hudi.apache.org/releases/release-1.2/#release-120

If you'd like to download the source release, you can find it here:
https://hudi.apache.org/releases/download#release-120

For details on how to use Hudi, please look at the quick start page located
at
https://hudi.apache.org/docs/overview#getting-started

We welcome your help and feedback. For more information on how to report
problems, and to get involved, visit the project website at
https://hudi.apache.org

Thanks to everyone involved!

- Ethan, Release Manager

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