What is
Vector Database?
A database optimized for storing and querying high-dimensional vectors (embeddings).
Definition
A vector database stores embeddings and supports fast nearest-neighbor search using approximate algorithms like HNSW or IVF. Common options include pgvector (PostgreSQL extension), Pinecone, Qdrant, Weaviate, and Chroma. The choice depends on scale, latency budget, hybrid-search needs, and whether you want a managed service.
Example
A RAG system stores 2 million document chunks as embeddings in pgvector and retrieves the top 20 most similar to a user query in under 100ms.
How Vedwix uses Vector Database in client work
For most clients we use pgvector — it lives next to the relational data, supports hybrid search with full-text indexes, and avoids managing a second system.
We ship this.
If you're building with Vector Database in production, we can help — from architecture review to full implementation.
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