Technology

Vector Stores

Vector Stores are specialized databases designed to efficiently store high-dimensional numerical embeddings, enabling rapid semantic similarity search for AI applications like Retrieval-Augmented Generation (RAG).

Vector Stores (or Vector Databases) are the core infrastructure for modern semantic search: they manage multi-dimensional vector embeddings, which are numerical representations of unstructured data (text, images, audio). Unlike traditional databases, they perform similarity searches—not keyword matching—using algorithms like HNSW (Hierarchical Navigable Small World) to find the closest vectors in the embedding space. This capability is critical for powering Large Language Model (LLM) applications, specifically in RAG systems, where external, up-to-date knowledge must be retrieved accurately. Key players in this space include open-source options like Milvus and Chroma, and managed services such as Pinecone and Weaviate.