Vector Search and Indexing in Azure SQL

I discuss how Azure SQL brings approximate vector search into relational workloads, including how indexing works alongside SQL filters and data changes. Product and engineering guests use demos to explain the feature’s capabilities and query-planning behavior.

- Customer needs and approximate nearest-neighbor search with the DiskANN index
- Searches combined with relational filters and joins, plus insert, update, and delete operations
- How the optimizer chooses between exact and approximate search, and a large-scale search demo
- The discussion focuses on Azure SQL’s vector index rather than a general survey of vector-search systems; the feature is announced as generally available

For developers and data professionals evaluating vector search in SQL, this provides an overview of the design and practical query patterns. Try the generally available Azure SQL vector index with a workload of your own to assess its fit.