While vector databases have gained prominence, the recent surge in generative AI, fueled by OpenAI’s ChatGPT launch, has thrust them into the limelight.

These specialized repositories handle vector data, crucial for applications like semantic search, chatbots, and recommendation systems.

However, a paradigm shift is under way: Why maintain a separate vector database when Azure SQL Database can seamlessly accommodate vector embeddings?

By integrating vector search into Azure SQL, you simplify application development, coexisting with operational data for efficient similarity searches, joins, and aggregations—all while leveraging Azure SQL’s robust features and sophisticated query optimizer.

In our session, we’ll showcase real-world examples of how Integrated Vector Search in Azure SQL Database enables AI-powered applications. You’ll learn how vector search outperforms traditional search methods.

Whether you’re a developer, architect, or data enthusiast, this session equips you to harness the power of vector embeddings within Azure SQL.