Vector Database
A specialized database designed to store and quickly search high-dimensional numerical representations of data (embeddings).
A Vector Database is a specialized storage system built to handle vector embeddings—complex numerical arrays that represent the semantic meaning of text, images, or audio.
In traditional relational databases, you search for exact keyword matches. In a vector database, you perform a "similarity search." When a user queries the database, their query is converted into a vector, and the database mathematically finds the stored vectors that are closest in "distance" to the query vector.
This allows AI systems to find documents that mean the same thing, even if they don't share any of the same words. Vector databases are the foundational infrastructure layer that powers Retrieval-Augmented Generation (RAG) systems.