AI
Choose and use a vector database
A vector database stores embeddings and finds the nearest ones to a query. RAG, semantic search, and recommendation systems use that lookup as their retrieval step.
For engineers comparing indexes and wanting a small retrieval workflow before they pick a hosted product.
Start here
Read the vector database overview, then complete the Qdrant basics tutorial with a few dozen of your own short texts.
Recommended resources
Start here · BeginnerWhat is a vector database?
Explains embeddings, similarity search, and why a dedicated index exists.
www.pinecone.ioBuild · BeginnerQdrant basics tutorial
A hands-on path for creating a collection, inserting vectors, and querying them.
qdrant.techReference · IntermediatePinecone overview
The hosted counterpart, useful when you are comparing operations rather than algorithms.
docs.pinecone.ioPrerequisite · IntermediateSentence Transformers quickstart
Shows how text becomes the vectors a database later stores.
www.sbert.netRelated topics
Learn retrieval-augmented generation · Evaluate a RAG system