Databricks launches Lakebase Search for agent-native retrieval

Databricks has introduced Lakebase Search, a new feature designed to enhance retrieval capabilities for AI agents. This hybrid vector and full-text search functionality is built directly into Lakebase Postgres, leveraging two new Postgres extensions: lakebase_vector and lakebase_text. The system aims to provide agent-first ergonomics by allowing agents to use a single data backend for their operational workloads, which differ significantly from human user needs. AI

IMPACT Enhances AI agent capabilities by providing efficient, agent-native retrieval directly within a data backend.

RANK_REASON Databricks announced a new product feature, Lakebase Search, which enhances existing database capabilities for AI agents.

Read on Databricks Blog →

• AWS
• Azure
• Hierarchical Navigable Small World graphs
• Jinjing Zhou
• Lakebase
• Lakebase Postgres
• Lakebase Search
• lakebase_text
• lakebase_vector
• PostgreSQL
• Pranav Aurora
• Zhou Sun

• product
• infra

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