vector-search-azure-sql

Stores and searches vectors natively in Azure SQL Database: the vector type, VECTOR_DISTANCE, the 1998 dimension ceiling, the DiskANN vector index, and the long list of places a vector column is refused. Use when a schema needs an embedding column, when someone asks to "store embeddings in SQL", "do similarity search", "cosine distance", "top k nearest neighbours", "CREATE VECTOR INDEX", "VECTOR_SEARCH" or "WITH APPROXIMATE"; when a vector column is rejected as a key, a constraint, a computed column or inside ORDER BY, GROUP BY, DISTINCT or UNION; and when a similarity query returns the right rows but scans the whole table. This skill owns the type and the query surface. The end to end pipeline is rag-on-azure-sql, generating embeddings embeddings-and-external-models, and a vector column's place in a wider design design-azure-sql-schema.