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A Practical Benchmark of Vector Databases for RAG
5 March 2026Artificial Intelligence

A Practical Benchmark of Vector Databases for RAG

After testing Pinecone, Weaviate, Milvus, and Qdrant with 100K documents, Qdrant proved the winner. While Pinecone was easy but costly (upwards of $750/mo), Weaviate struggled with slow updates, and Milvus required heavy infrastructure. Qdrant stood out for its speed, built-in UI, and quantization features that cut memory usage by 60%, offering the best balance of performance and cost-efficiency for RAG applications.

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