Vector Databases: Deep Indexing and Token Economics Explained

This tutorial covers where embeddings are stored, how indexing methods like IVF and HNSW speed up search, and how product quantization reduces memory. It also discusses metadata indexing and token economics to avoid duplicate costs. The guide uses pgvector as a practical example for building scalable vector search systems.