Graph Engines
Graph engines run graph computation over data stored in other systems, projecting nodes and relationships on the fly instead of requiring you to move everything into a standalone graph database.
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Memgraph
Diamond sponsor
Memgraph is a high-performance, in-memory graph database built for real-time AI context and graph analytics. It serves as the graph engine for GraphRAG pipelines, AI memory systems, and agentic workflows, delivering sub-millisecond multi-hop traversals with full provenance for systems that need structured, connected context alongside semantic search. The same architecture powers real-time graph analytics across fraud detection, network analysis, infrastructure monitoring, and other operational use cases.
Neo4j
Diamond sponsor
Neo4j is the knowledge layer for enterprise AI. Powered by the Neo4j Graph Intelligence Platform, Neo4j connects organizational data with humans and AI systems, surfacing not just relationships, but how and why they exist. The result is AI that is accurate, explainable, and governable. Built to integrate with everything. Proven by 84 of the Fortune 100 and supported by the world’s largest graph community, Neo4j helps organizations move AI from pilot to production.
This catalog focuses on current graph engines and co-processors that operate over existing data platforms. To be included, an offering has to meet three criteria:
No primary graph storage of its own
- It is not a general-purpose graph DBMS and does not act as the primary system of record for graph data. Instead, it runs graph computations over data stored in other systems, such as warehouses, relational databases, event streams, or embedded platforms.
Graph computation layer over existing platforms
- Its main role is to project a graph model onto existing data and run graph algorithms, traversals, or reasoning there, typically with minimal or no ETL. Examples include Snowflake-native coprocessors, graph engines running on SQL warehouses, and streaming graph engines running on Kafka or Kinesis.
Exposes graph query and analytics as a service
- It provides a programmable graph engine interface, via query languages and/or graph algorithm APIs, for pattern matching, traversals, centrality, community detection, pathfinding, and related workloads, independent of any particular visualization UI.
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The table summarizes these tools across key dimensions so you can quickly see where each product fits and which merit a deeper look.