What Is a Vector Database?
A vector database stores and searches embeddings — high-dimensional vectors — to find the most semantically similar items quickly, powering RAG, semantic search, and recommendations.
A vector database is a database designed to store and search embeddings — high-dimensional numerical vectors — and to quickly find the vectors most similar to a query.
Why it matters
Traditional databases match exact values; vector databases match meaning. This makes them the storage layer for semantic search, retrieval-augmented generation, and recommendation systems, where you need the closest matches by similarity, fast, at scale.
Common options
Pinecone, Weaviate, Qdrant, and pgvector (a PostgreSQL extension) are widely used. Some search engines like Elasticsearch also support vector search. The right choice depends on scale, latency, cost, and whether you need hybrid keyword + semantic retrieval.
Related
See embeddings and RAG development.
Ready to turn your data into measurable growth?
Book a free consultation with Apex Data Cloud. We serve Orlando, Central Florida, and clients nationwide.