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The world’s most innovative companies use graph databases to achieve real-time data insight for critical use cases like fraud detection, recommendation engines, AI and machine learning, and customer 360. But not all graph databases are created equally. Unlike traditional graph databases, TigerGraph can scale for real-time multi-hop queries spanning trillions of relationships. This graph database benchmark study examines the data loading and query performance of TigerGraph, Neo4j, Amazon Neptune, JanusGraph, and ArangoDB. TigerGraph is 2x to more than 8000x faster at graph traversal and query response times compared to other graph databases tested, running on a single server.