Enterprise RAG with pgvector

🛠 Lab from the AI Platform Engineering Bootcamp. Used in Week 3. Bootcamp landing page: https://academy.tekanaid.com/bootcamps/ai-platform-engineering-bootcamp Parent course(s):

• Week 3: RAG Architectures and Vector Databases (slug: rag-architectures-103)

🟡 Beta bootcamp lab. Hands-on instructions, check scripts, and solve scripts are in place. Lab is part of the running Platform Assistant capstone arc that grows across all 8 weeks of the bootcamp.

This optional lab teaches you to use PostgreSQL with the pgvector extension for vector similarity search in RAG systems.

You'll learn to:

• Deploy PostgreSQL with pgvector on Kubernetes
• Create optimized vector indexes using HNSW
• Build a complete RAG pipeline using pgvector
• Compare performance between pgvector and Chroma
• Understand when to choose pgvector for enterprise RAG

pgvector is ideal for organizations already using PostgreSQL who want to add vector search without introducing new infrastructure.