memgraph

Why we included this project

Memgraph is an in-memory graph database designed for AI systems that need to combine connected, structured data with similarity search in a single query. Instead of stitching a vector index onto a separate relational store, it executes Cypher traversals, full-text matches, and vector lookups atomically, which makes it a natural fit for GraphRAG retrieval, agent memory, and real-time analytics on networks or transactions. Teams already fluent in Neo4j's Cypher dialect can move over without re-learning query syntax, and the engine targets sub-millisecond multi-hop traversals for latency-sensitive workloads. For anyone building LLM or agent pipelines, it fills the practical gap of where to persist and query the relational context those models depend on.