Microsoft Developer showcases the new vector search and embedding features in SQL Server 2025 and Azure SQL Database, revealing how database developers can enable semantic and natural language search within their data systems.

Smarter Queries Start Here: Vector Search in SQL Server & Azure SQL DB

Presented by: Microsoft Developer

Overview

SQL Server 2025 and Azure SQL Database introduce support for vector search and embeddings. This session demonstrates how developers and database professionals can harness these new capabilities to enable smarter, more relevant searches with semantic and natural language queries—all from within their existing database platforms using T-SQL.

Key Topics Covered

• Vector Search in SQL Server & Azure SQL DB: Learn how vector-based search makes database queries more intelligent, enabling similarity searches and contextual recommendations instead of relying solely on keyword matching.
• Storing and Indexing Embeddings: See how to store vector embeddings within your database tables and index them for efficient search.
• Querying with Familiar T-SQL Syntax: Discover how to use standard T-SQL extensions to execute vector-based searches and work with semantic data.
• Practical Use Cases: Real-world scenarios showcase practical applications such as recommendation engines, natural language interfaces, and semantic data navigation.
• Integration with AI and ML: Understand how these database capabilities connect with machine learning workflows, making it easier to operationalize AI-driven features directly within your data tier.

Real-World Example Scenarios

• Building a product recommendation engine directly in the database
• Supporting natural language search in business applications
• Enhancing knowledge base or document search with semantic retrieval

Getting Started

1. Prerequisites:
   • Access to SQL Server 2025 or Azure SQL Database
   • Basic understanding of T-SQL
2. Step-by-Step Guidance:
   • How to create embedding columns
   • How to use vector indexes
   • Example queries using new T-SQL vector functions

What You'll Learn

• Why vector search is foundational for modern AI-powered applications
• How to set up and use embedding/vector search in your database today
• Best practices for integrating these capabilities with your existing solutions

Additional Resources

• Official Microsoft documentation on SQL Server 2025 vector search
• Tutorials and quickstarts for Azure SQL Database vector operations

Conclusion

By leveraging the new vector search and embedding features, developers can unlock next-level search and recommendation power directly within their Microsoft SQL databases, preparing their apps for an AI-driven future.