Building Intelligent Search with SQL and Vector Search

Modern applications require smarter search capabilities that go beyond simple keyword matching to understand user intent. This text-based course guides you through building intelligent, semantic-aware search systems directly inside your SQL databases. You will transition from basic querying to designing advanced hybrid search architectures. By combining traditional relational indexing with modern vector search techniques in systems like SQL Server and Azure SQL, you will learn how to retrieve highly relevant results for complex user queries. What you'll learn: - Understand the foundational differences between keyword-based full-text search and semantic vector search - Prepare SQL databases to store, index, and query high-dimensional vector embeddings - Implement hybrid search patterns that combine keyword matching and semantic results - Apply ranking algorithms and reciprocal rank fusion to score and sort search results - Explore how modern SQL search integrates with retrieval-augmented generation (RAG) and AI workflows The course starts with essential search terminology and database indexing fundamentals before moving into vector math basics and practical SQL implementation patterns. You will read clear explanations and study well-structured SQL code snippets to build your search systems step-by-step. Designed for database developers, data engineers, and software creators new to vector search, this program requires no prior AI experience. Start reading today to unlock the power of intelligent search in your SQL databases.