AlloyDB AI with pgvector for RAG: SQL-Native Vector Search on GCP with Terraform 🔎

RAG Engine's managed Spanner DB is simple but opaque. AlloyDB AI gives you pgvector with Google's ScaNN index, built-in Vertex AI integration, and full SQL control over your vectors. Here's how to set it up with Terraform for RAG workloads. In RAG Post 1 , we deployed a Vertex AI RAG Engine corpus backed by RagManagedDb, a fully managed Spanner-based vector store. It's zero-config, but you can't see your vectors, can't run SQL against them, and can't combine vector search with your existing relational data. AlloyDB AI is GCP's alternative: a fully managed PostgreSQL-compatible database with pgvector for vector operations, Google's ScaNN index for high-performance similarity search, and built-in Vertex AI integration that lets you generate embeddings directly in SQL. If you already have relational data and want to add vector search without a separate system, AlloyDB is the answer. This post covers the Terraform setup and RAG patterns. 🎯 🔍 Why AlloyDB AI for RAG? The RAG Engine managed D