Vector databases represent the critical search foundation of modern enterprise RAG systems. In this benchmark, the Radar Hardware Lab evaluates Qdrant, Milvus, pgvector, and Pinecone over a standardized dataset of 10 million 1536-dimensional embeddings. We analyze throughput, P99 tail latency, memory overhead, and scalar filtering speed.
Vector Database Performance Benchmarks 2026: Qdrant vs Milvus vs pgvector vs Pinecone under 10M Vectors
✦ Executive Research Brief · Hardware-Verified in Radar Lab ✦
A 10-million vector stress test comparing Qdrant, Milvus, pgvector, and Pinecone. We benchmark QPS under high concurrency, P99 query latency, HNSW build times, scalar filtering speed, and infrastructure TCO.