AI Developer (Level 7)
Topic Guide · 2026
Vector Databases
Vector database guide — Pinecone, Qdrant, Weaviate, Chroma and pgvector compared for RAG and semantic search in 2026.
Quick Answer
A vector database stores embeddings (numeric representations of text) and finds semantically similar items in milliseconds. It is the storage layer of every RAG system.
What you'll learn
- What embeddings are
- ANN search: HNSW, IVF, PQ
- Filtering, hybrid search, metadata
- Pinecone vs Qdrant vs Weaviate vs pgvector
- Hosted vs self-hosted
- Scaling to 100M+ vectors
Recommended tools
PineconeQdrantWeaviateChromapgvectorMilvus
Frequently asked questions
Which vector database should I use?+
Qdrant for self-host and best price/perf. Pinecone for zero-ops hosted. pgvector if you already run Postgres. Weaviate for hybrid graph + vector search.
Do I really need a vector DB?+
For under 10,000 chunks — no, in-memory or SQLite works. Above that, yes, or your latency and cost fall apart at scale.
Want Vector Databases training for your team?
Nirmal Rabari delivers this topic as a live corporate workshop across India, UAE, UK and US.