Vergleichende Analyse von Vektor-Datenbanken für Chatbot-Anwendungen

Four vector databases (FAISS, Chroma, Qdrant, Weaviate) and four embedding models were benchmarked on one million text snippets for speed, accuracy and memory use.
Results show clear trade-offs: FAISS delivers the best recall, Chroma the lowest latency, Qdrant the smallest footprint, while an added smart router can automatically pick the best engine for each query.