Uses "pointer chasing" to traverse nodes and edges. Each hop requires a separate memory lookup, which slows down significantly as the network grows.
According to technical breakdowns by experts like Avi Chawla and Akshay Pachaar , the performance gap comes from how data is processed:
For anyone building or real-time AI agents, this level of latency reduction could be a game-changer.
496x faster alternative to Neo4j…(open-source) | Avi Chawla
Represents the entire graph as a sparse matrix . It translates complex traversals into parallelized linear algebra operations (matrix multiplication), allowing the CPU to process multiple paths simultaneously. Sample Post for "496x" If you are looking to share this update, Headline: Is Neo4j finally being challenged? 🚀
It processes thousands of paths at the same time instead of hopping through memory.
A new open-source player, , just dropped a bombshell: it’s 496x faster than Neo4j.
