Vector Database
A specialized database designed to store and query high-dimensional vector embeddings, crucial for AI search and memory.
A Vector Database is a highly specialized data storage system designed specifically to handle vector embeddings - mathematical representations of unstructured data (like text, images, or audio) generated by machine learning models.
Unlike traditional relational databases that search for exact keyword matches, vector databases perform "similarity searches." They can rapidly find the vectors that are mathematically closest to a given query vector.
This capability is the absolute backbone of Retrieval-Augmented Generation (RAG). When an enterprise Large Language Model needs to "look up" corporate documents to answer a question, it queries a vector database to find the most semantically relevant information.