Introduction to pgvector

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The module introduces the pgvector extension for Azure Database for PostgreSQL, covering learning objectives and explaining how pgvector adds vector types and similarity operators to PostgreSQL, enabling semantic search and RAG scenarios without a separate vector database.

Previous Module Introducing Azure Database for PostgreSQL

This Module AI Vector Search on PostgreSQL

Introduction to pgvector

Store and Query Embeddings with pgvector

Vector Similarity Search Indexes

Vector Similarity Search for Semantic Retrieval

Retrieval Patterns for RAG Pipelines

Optimize Vector Search in Azure Database for PostgreSQL

Tune PostgreSQL for pgvector

Choose and Configure Vector Indexes

Optimize Data Layout for Filtered Search

Scale PostgreSQL for High-Volume Workloads

Connection Optimization with PgBouncer

Next Module Introducing Azure Managed Redis