The Database Zoo: Vector Databases and High-Dimensional Search

Vector databases are purpose-built engines for high-dimensional similarity search, optimized for workloads like semantic search and recommendation systems. They use specialized indexing techniques like HNSW and compression methods to handle billions of embeddings efficiently. The article explains architecture differences from general-purpose databases, core storage layouts, and query execution patterns.