Trillion edges benchmark: new world record beyond 100TB by TigerGraph featuring AMD based Amazon EC2 instances

Graph databases have gained popularity due to their ability to handle complex, interconnected data. TigerGraph, a leading graph database solution, has recently set a world record for handling big graph workloads in a real-world production environment on AWS using 72 R6a.48xlarge Amazon Elastic Compute Cloud (Amazon EC2) instances powered by 3rd Gen AMD EPYC CPUs. TigerGraph successfully processed complex, deep-link OLAP-style queries on a massive graph containing 217.9 billion vertices and 1.6 trillion edges. This capability to scale in graph analytics and business intelligence on graph-structured data up to hundreds of terabytes is a game-changer in the world of big data, making TigerGraph an ideal solution for enterprises seeking to analyze intricate, interrelated data on a massive scale.