Database upstart TigerGraph has launched its latest platform, pitching the ability for enterprise customers to collaborate in real time.
The business was founded in 2012 but only came out of stealth in September. Today it is launching its 2.0 platform, which it says offers more collaboration, and faster performance, than other graph databases.
Having flown relatively under the radar recently – privately-funded Neo4J has had the market mostly to itself for more than a decade – graph databases are firmly planted in the mainstream these days.
TigerGraph founder Yu Xu told The Register that 2018 would be "the year of the graph". Graph theory isn't new, he said, but graph database was a niche market until the age of big data.
"At the start, people were just happy to store data... then they started to think about simple analytics... then started talking about a method for simplified computation," Yu said.
"People realised that to connect the dots, a graph database is best – [so] graph database and big data started to merge. Everything is coming together, which is why we're seeing such a big movement."
This is emphasised by the increase in traditional vendors offering graph databases – Microsoft's Cosmos is ranked second behind Neo4J in DB Engines' graph DBMS ranking, and AWS launched Neptune in November.
TigerGraph claims to out-compete these legacy and traditional vendors by offering a distributed, parallel graph computing platform that runs faster queries and uses less space to store the data. It promises to load 50 to 150GB of data per hour, per machine and traverse hundreds of millions of vertices/edges per second per machine.
"We define real-time as data coming in, being able to process that data in less than a second and being able to take action on that data in that business moment," said chief operating officer Todd Blaschka.
The database is pitched firmly at enterprise customers that they hope will buy into the idea of genuinely real-time processing of very large data sets, for instance recommendations engines and fraud detection.
Customers include major e-commerce firms Alipay, Visa and Wish, along with Uber and the State Grid of China.
Blaschka claims that Alipay has "arguably the world's largest graph database on TigerGraph for its anti-money laundering business". It streams 2 billion events in real-time, he said, with the graph having over 100 billion vertices and 600 billion edges on a cluster of 20 machines.
The latest release pushes more enterprise upgrades, with the main focus being real-time graph collaboration through what it calls multi-graph.
The idea is that multiple groups – like product, recommendations and security teams – can share one master database and benefit from real-time updates to that underlying data.
The biz said that local control and security settings would ensure the customer still meets data compliance regulations, as it will be able to dictate who can access which data.
"With TigerGraph, we're able to provide different views working off the same underlying database, and as data in one batch of the database gets updated, all those groups will benefit in real time," Blaschka said.
The biz says that while multi-tenancy "enforces data silos", multi-graph supports multiple people using the same underlying data set.
"There's a significant performance enhancement because it will give customers more access to data to analyse, and make new business decisions they wouldn’t have before – or that it was very time consuming to do," said Blaschka.