Vector Database
A database built to store and search embeddings — the numerical representations of meaning that let AI find similar content.
01 Definition
A vector database stores embeddings (numerical representations of text, images, or other data) and is optimized to quickly find the closest matches by meaning, rather than by exact keyword match — the backbone of most RAG systems and AI-powered search.
02 Why It Matters
This is the infrastructure that lets an AI tool search 'by meaning' across thousands of documents instantly — without it, RAG and semantic search wouldn't be practical at scale.
03 Example
A customer-support AI searching a vector database of past support tickets to find similar past issues.