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TigerGraph nabs $31M in Series A funding
Tuesday, September 19, 2017
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Richard Harris |
SQL Graph database company TigerGraph, formerly GraphSQL, has nabbed $31M in a Series A funding round.
TigerGraph has made announcements including its emergence from stealth, securing of $31M in Series A funding, general availability of TigerGraph, and availability of both its Cloud Service and GraphStudio. Their Native Parallel Graph Technology (NPG) powers real-time deep link analytics for enterprises with complex and colossal amounts of data.
Formerly known as GraphSQL while in stealth, TigerGraph is a technical breakthrough representing the next stage in the graph database evolution - a complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time.
Graph Databases are the fastest growing category in all of data management, according to DB Engines. However, first generation solutions are not designed to support the massive data volumes and data creation rates enterprises face and are unable to provide the full benefits of graph analytics.
- 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.
- Massive Scale: 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.
"We are very excited to publicly launch our product after being battle tested by the largest customers in the world," said Yu Xu, founder and CEO of TigerGraph. "With the power of combining real-time, big data and deep link analytics in a single platform, TigerGraph delivers the true promise and benefits of a graph platform. We expect to see a slew of new enterprise applications powered by TigerGraph. TigerGraph is poised to redefine the enterprise market just as the iPhone redefined the smartphone market."
Formerly known as GraphSQL while in stealth, TigerGraph is a technical breakthrough representing the next stage in the graph database evolution - a complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time.
Graph Databases are the fastest growing category in all of data management, according to DB Engines. However, first generation solutions are not designed to support the massive data volumes and data creation rates enterprises face and are unable to provide the full benefits of graph analytics.
Key Features
- 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.
- Massive Scale: 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.
"We are very excited to publicly launch our product after being battle tested by the largest customers in the world," said Yu Xu, founder and CEO of TigerGraph. "With the power of combining real-time, big data and deep link analytics in a single platform, TigerGraph delivers the true promise and benefits of a graph platform. We expect to see a slew of new enterprise applications powered by TigerGraph. TigerGraph is poised to redefine the enterprise market just as the iPhone redefined the smartphone market."
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