How HNSW Indexes Millions of Vectors

Data & AI Pipelines diagram · made in Skemio

Architecture diagram illustrating HNSW vector indexing layers from sparse top layer highways down to dense bottom layer local connections.

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What it shows

Organizes vectors into hierarchical multi-layer skip-list graph structures.
Top layers have sparse connections for rapid coarse-grained exploration.
Bottom layer (Layer 0) holds all vectors with dense local neighbor links.

The takeaway

HNSW trades small memory overhead for logarithmic nearest neighbor search speeds in high dimensions.

#VectorSearch
#HNSW
#VectorDatabase
#Algorithms
#RAG
#DataStructures

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