New Course: SQL Server 2025 Vector Search Essentials
When keywords fail and intent matters.
I spent the last three months building a course about vector search in SQL Server 2025. Paul Randal announced it today. I’m back with SQLskills for this one, and it’s the first in their new AI-focused course library.
Vector search is showing up in more places: product recommendations, natural language queries, support ticket clustering, code search. The common thread is meaning over keywords.
Search for “outdoor enthusiast home” in a property listing database. Keyword search may fail in absence of the word “outdoor” in the property description. Vector search finds “walking distance to parks and trails,” “mature landscaping,” “private balcony.” Vector search matched meaning, not text.
SQL Server 2025 brings native vector search to the platform many of us have worked with for decades. You don’t need a separate vector database or a new operational model.
Who This Is For
Database professionals who want to understand vector search without becoming data scientists. If you manage SQL Server environments, work with application teams, or need to evaluate whether vector search fits a workload, this course gives you the foundation. If you understand indexes and query plans, you’ll understand vector indexes and distance calculations.
What the Course Covers
The AIVSE course starts with how text becomes vectors and builds through distance calculations, indexing with DiskANN, hybrid search patterns, and production deployment with external models and capacity planning. The course uses SemanticShoresDB, a sample database with 100,000 property listings and pre-generated embeddings.
By the end, you’ll know when vector search makes sense for a workload and how to implement it in SQL Server 2025.
Details
Paul’s announcement covers pricing and a limited end-of-year discount for Blackbelt and newsletter subscribers. I hope you’ll check it out.