The user wants me to rewrite a headline about comparing four vector databases. Let me analyze the original:

Short summary

Four major vector databases excel at different constraints: Pinecone for zero-ops managed service under 10M vectors, Qdrant for best filtering and native hybrid search, Weaviate for vectorization and multi-modal, Milvus for billion-scale datasets. Qdrant and Weaviate maintain high recall under selective filters. Real-world tradeoffs emerge in cost, latency (Qdrant 4ms p50 vs Pinecone 20-30ms), filtering quality, and scaling needs—not in day-one functionality.

• •Pinecone: zero infrastructure, no ops complexity, best under 10M vectors
• •Qdrant: best filtering during traversal, native hybrid search, lowest cost at scale
• •Weaviate: built-in vectorization, multi-modal support, mature BM25+dense implementation
• •Milvus: only option for 100M+ vectors, GPU acceleration, requires Kubernetes

Generated with AI, which can make mistakes.