Open source vector database supplier Qdrant has developed its own BM42 search algorithm combining vector and standard BM25 keyword search methods to get better RAG results, claiming the method lowers cost. A vector database stores encoded tokens (vector embeddings) representing parts of text phrases, audio, image, and video streams, which a large language model (LLM)