Lakebase Search brought native vector and hybrid search to Postgres on AWS and Azure.

In September 2026, search capabilities expanded with the general availability of Lakebase Search on AWS and Azure [1]. The update added native keyword, vector, and hybrid search directly to Postgres, enabling teams to query operational data without maintaining separate data transfer pipelines [1]. Meanwhile, developer tooling advanced with release v1.17.0, which added AI Gateway service support into deployment bundles alongside direct deployment state updates requiring newer CLI versions [4].

Practitioners encountered practical integration challenges when working with automated search workflows. Users reported issues where Knowledge Assistant failed to load following indexing tasks, leaving the generated AI Search index locked and unable to be reused across other applications [2]. At the same time, developers documented deployment patterns for connecting Genie agents with Azure AI Foundry using bundles [7], while enterprise reports showed Genie helping analysts process centralized data at organizations like adidas [3].

Broader architectural discussions centered on expanding retrieval patterns beyond standard vector stores. Community sessions explored combining graph databases with Retrieval-Augmented Generation workflows using Neo4j and Cypher alongside autonomous agents [5]. Developers also debated potential native agent composer interfaces to simplify how teams build agents directly from lakehouse assets [6].