Vector Database
Data/dictionary/vector-database
Definition
A database optimised for storing and searching embeddings — finding the K nearest vectors to a query vector. Examples: Pinecone, Weaviate, pgvector. The retrieval engine in most RAG systems.
Posts that use this term
- Agent memory: scratchpad vs long-term store
An agent forgets everything the moment its context window ends, unless something is built to save it. Short-term scratchpad vs a real long-term store, and what's actually worth keeping.
- Beyond vector search: hybrid, rerank, and graph RAG
When plain vector search hits its ceiling, three upgrades actually help: hybrid search, reranking, and graph RAG. When each one earns its added complexity.
- Local RAG and embeddings
Build a working local RAG pipeline in about 30 lines using nomic-embed-text, Chroma, and Llama 3.2. And why running it on your own machine beats the cloud for personal notes.
- Prompt, RAG, fine-tune: three ways to shape a model
Three levers for shaping what an LLM does: prompting (ask better), RAG (give it the right context), fine-tuning (change the weights). What each costs, what each fixes, and how to pick.
- RAG: giving a model memory it doesn't have
RAG is the pattern of fetching relevant text from a search system and putting it in the LLM's context window before asking your question. Not magic, not fine-tuning, just better prompts.