A multi-line description of two to three lines explaining what the post covers: what an embedding represents, dense vs sparse vs hybrid retrieval, HNSW and IVF-PQ ANN indexing, and where ranking quality actually lives.
Vector-Search
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Embedding Models and Vector Search, Honestly -
Local Vector Search for Homelab RAG: pgvector vs Qdrant vs Chroma A practical comparison of Chroma, pgvector, and Qdrant for fully self-hosted vector search — covering setup, embedding generation on local hardware, and wiring each into an offline RAG stack that never phones home.