TigerGraph is emerging from stealth, securing of $31M in Series A funding and launching TigerGraph - a native parallel graph database platform for enterprise applications along with the availability of both its Cloud Service and GraphStudio, TigerGraph’s visual software development kit (SDK).
TigerGraph’s Native Parallel Graph Technology (NPG) powers real-time deep link analytics for enterprises with complex and colossal amounts of data.
With investors including Qiming VC, Baidu, Ant Financial, AME Cloud, Morado Ventures, Zod Nazem, Danhua Capital and DCVC, TigerGraph’s $31 million in funding is one of the most sizeable financing rounds in graph database history.
Formerly known as GraphSQL while in stealth, TigerGraph is a breakthrough representing the next stage in the graph database evolution, according to the company. The platform is a complete, distributed, parallel graph computing platform that supports web-scale data analytics in real-time.
TigerGraph is the real-time graph database platform for enterprise. TigerGraph is especially suited for very large graphs - the best model for deep link analytics as they enable exploration, discovery, and prediction of relationships.
Additionally, TigerGraph’s architecture is modular and supports both scale-up and scale-out deployment models for distributed applications.
Performance features of the new platform include real-time deep link query speed, real-time graph loading, and massive scale.
Uses cases can include anti-fraud and anti-money laundering, customer intelligence, supply chain intelligence, and smart grid.
Customers who work with large sets of data and need fast loading will benefit the most from this platform, according to Yu Xu, CEO and founder of TigerGraph.
Xu sai the company will introduce new features to their cloud offering along with more support for various query languages in the near future.
For more information about this news, visit www.tigergraph.com.