Power the next generation of AI apps with databases at scale anywhere
summary
Announcements show SQL and MySQL getting interactive Copilot chat and natural language to T‑SQL that generate complex queries; Cosmos DB adds vector search with DiskANN for 25 ms retrieval and unified operational vectors; PostgreSQL runs in‑database embeddings (E5-tech-small) with single‑digit ms latency; automatic index tuning for Postgres surfaces creates/drops with ~82% forecasted speedup; Data API Builder turns stored procedures into REST/GraphQL endpoints; Hyperscale claims include 68% faster SQL at high concurrency and MySQL 26× speed versus competitors. Public preview and GA timelines vary.
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chapters (15)
- 0:00Introduction
- 6:51Microsoft’s data platform for AI
- 14:28Cloud-scale databases for AI
- 15:56Intelligent databases with AI
- 17:45Copilots and natural language for SQL
- 19:13Vector search in Cosmos DB
- 24:18PostgreSQL for AI workloads
- 26:50Automatic index tuning in PostgreSQL
- 31:30Managed databases with AI services
- 34:41Azure AI extensions for PostgreSQL
- 35:46Data API Builder
- 36:30AI apps with Azure SQL and Data API Builder
- 40:50Security for AI databases
- 43:20Threat protection for databases
- 44:29Summary and future
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