Vector search lands in Apache Hudi lakehouses

Apache Hudi is adding vector search to its lakehouse platform, letting teams run semantic queries directly on raw data without moving it into a separate vector database.

The feature plugs into Hudi's existing table formats, so data stays in the same place it was ingested. Teams can store embeddings alongside structured columns and query them with similarity search. The move reduces the plumbing between ingestion, storage, and retrieval.

Hudi is open source. The lakehouse angle means you keep data governance and auditing in one place instead of juggling a data warehouse, a lake, and a vector store.

This is not a new product. It is an update to the toolset you already use if you are building data pipelines at scale.

Why this matters for us: the engineering teams that decide which tools our small shops and startups get to use are the ones who control the cost of data infrastructure, and this keeps one less paid service in the way.