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Distributed retrieval distributes indexes and queries across multiple nodes to support large-scale document volumes and high-concurrency queries; common practices include vector index sharding, replica redundancy, approximate nearest neighbor (ANN) algorithms (such as HNSW and IVF), and query aggregation and reranking.
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10/20/2026
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Related Claims
UnverifiedMainstream ANN index structures include HNSW, IVF, and ScaNN proposed by Google, with different index structures presenting different trade-offs among recall rate, query latency, and memory usage.72% similarUnverified主流向量库采用HNSW、IVF等索引算法来解决高维空间近似最近邻搜索问题71% similarUnverifiedMainstream vector databases such as Pinecone, Weaviate, Qdrant, and pgvector generally adopt the HNSW approximate nearest neighbor indexing algorithm at their core.70% similarUnverifiedStorage-compute separation means deploying the data persistence layer and the compute layer independently and scaling them independently; in a search system, index building, merging, and query serving can run on different node pools while sharing the same S3 data.69% similar
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