SQL Server 2025 introduces vector data types and functions, enabling native AI-driven similarity searches and machine learning tasks directly in SQL queries without external tools.
Key AI Features
Vector data types store embeddings as optimized binary JSON arrays for efficient operations like distance calculations (e.g., VECTOR_DISTANCE, VECTOR_NORM). New vector indexes support approximate nearest neighbor searches, accelerating AI workloads. External AI model management allows invoking REST endpoints for embeddings via sp_invoke_external_rest_endpoint.
Developer Enhancements
Regular expressions functions like REGEXP_LIKE and REGEXP_REPLACE enable pattern matching and text manipulation in queries. Fuzzy string matching with EDIT_DISTANCE_SIMILARITY computes similarity scores for approximate searches. Change event streaming captures real-time DML changes to Azure Event Hubs in JSON or Avro formats.
Performance Improvements
Optimized locking reduces blocking and memory use, while tempdb governance prevents space exhaustion from runaway jobs. Cardinality estimation feedback for expressions adapts query plans across executions, and optional parameter plan optimization (OPPO) handles varying parameters dynamically. These align with 2025 trends like AI integration and query tuning for modern data stacks
No comments:
Post a Comment