Databricks introduces batch vector search for massive datasets

Databricks has added an engine-native vector search feature designed to handle massive batch jobs—instead of just fast real-time queries. The update lets you run millions of queries against millions or even billions of vectors in one go, making it much easier to tackle large-scale jobs like deduplication, semantic tagging, and transaction matching. The feature is tightly integrated into the Databricks Runtime and optimized for high throughput and reliability across distributed cloud environments.

• Aimed at batch, not real-time vector search
• Scales to billions of database records
• Optimized for high throughput and distributed computing
• Handles workloads like entity resolution and batch tagging