Single-Store Vector Index: Architecture and Memory Efficiency
Blog post from Memgraph
Memgraph's single-store vector index is an integrated component within the same storage engine as the graph, designed to enhance memory efficiency and operational scalability for vector search. Utilizing a USearch-backed structure, the index is keyed by vertex pointers and employs a configurable metric and scalar kind, allowing for precision-memory trade-offs. This design avoids duplicate vector storage by maintaining the vector data as a single copy within the index, ensuring that concurrency and durability are inherently supported. In recent updates, Memgraph has optimized the memory layout, achieving a substantial reduction in RAM usage—approximately 66-76% less—while maintaining the same workload efficiency, as demonstrated in benchmarks with one million nodes and 1024-dimensional embeddings. These improvements enable larger workloads to be run on the same hardware or the same workloads on smaller instances, without incurring additional RAM costs.