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 Semantic search is no longer a “nice-to-have” feature. Modern applications are expected to understand meaning , not just keywords. With SQL Server 2025 introducing native vector support and EF Core 10 enabling first-class integration , .NET developers can now build powerful semantic search systems without external vector databases . This article walks through how modern semantic search works , why SQL Server 2025 changes the game, and how you can implement it cleanly using EF Core 10 . What Is Semantic Search? Traditional search matches exact words . Semantic search matches intent and meaning . Example: Query: “Affordable cloud training” Result: “Low-cost AWS certification course” Even though the words differ, the meaning is the same . This is achieved using vector embeddings —numerical representations of text that capture semantic relationships. Why SQL Server 2025 Is a Big Deal Until now, semantic search in .NET usually required: Azure Cognitive Search Pineco...

Optimizing SQL queries is one of the fastest ways to improve application performance without upgrading hardware or redesigning systems. As databases grow and applications scale, even a small inefficiency in a query can result in massive performance drops. This is why SQL Server developers must understand not just how to write queries, but how to make them efficient, predictable, and scalable. This article highlights the most valuable query optimization techniques every SQL Server developer should master. Consider it your practical guide to writing faster SQL and reducing server load                                  1. Understand How the Query Optimizer Thinks SQL Server’s Query Optimizer is a cost-based engine. Its goal is simple: find the least expensive execution plan based on available statistics, indexes, and schema. As a developer, your job is to give the optimizer everything it needs: Clea...