29 Sep Introducing TigerGraph, a Native Parallel Graph Database
By Yu Xu, TigerGraph founder and CEO
Today we proudly launch TigerGraph, a ground-breaking technology built from the ground up to address a critical pain point: the need for real-time analytics for enterprises with massive amounts of data.
I was first exposed to this need as a college student in China working with companies with massive amounts of data. My journey to find a solution to the problem brought me to the United States, where I received my Ph.D. from UC San Diego, followed by my work at Teradata and Twitter.
Graph databases offer considerable benefits, but solutions thus far have missed the mark in delivering upon the promise of graph analytics. Indeed, first generation graph databases were never designed to support current enterprise challenges of massive and complex big data.
TigerGraph was born to achieve this. Whereas other solutions are limited to traversing two hops in big data graph queries, TigerGraph provides a robust enterprise platform for Deep Link Graph Analytics (DLA) which requires three hops or more along with fast query response time.
How is TigerGraph able to do this? By offering the world’s first and only Native Parallel Graph (NPG) – a solution that focuses on both storage and compute to support real-time graph updates and built-in parallel computation. TigerGraph is a complete, fully distributed graph analytics platform. Its performance features include:
Real-Time Deep Link Query Speed.
The ability to traverse hundreds of million of vertices/edges per second per machine traversing three hops or more, orders of magnitude faster that traditional approaches.
Real-Time Graph Loading.
The ability to load 50 to 150 GB of data per hour per machine. No more batch loading!
The ability to stream 2B+ daily events in real-time to a graph with 100B+ vertices and 600B+ edges on an only 20 commodity machine cluster, battle-tested by the world’s largest e-payment company with over two years in production.
TigerGraph supports real-time analytics for the largest datasets, including: fraud prevention at the world’s largest e-commerce provider, recommendations at the world’s largest mobile e-commerce company, and network management at the world’s largest electric grid company. Our customers include brand-names such as State Grid Corporation of China, Wish.com and Elementum.
Along with our product, TigerGraph also today announced $31 million in Series A funding – one of the most sizeable financing rounds in graph database history, and the launch of our Cloud Service on Amazon EC2. To learn more, visit: www.tigergraph.com.
I look forward to continuing the TigerGraph journey and invite you to join us as we define the next stage in the graph database evolution.
Together we can help enterprises roar with the power of real-time analytics over their complex and massive amounts of data – providing competitive business advantages like never before.