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Redwood City-based TigerGraph, a developer of database software used for data analytics, said this morning that it has raised $31M in a Series A funding. The funding came from Qiming VC, Baidu, Ant Financial, AME Cloud, Morado Ventures, Zod Nazem, Danhua Capital and DCVC. The company–formerly known as GraphSQL–is led by Yu Xu.
The company says it has developed a complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time.
TigerGraph nabs $31M in Series A funding
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.
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
TigerGraph Emerges with Native Parallel Graph Database
A startup named TigerGraph emerged from stealth today with a new native parallel graph database that its founder thinks can shake up the analytics market. With $31 million in venture funding and several high-profile customers, he might just be right.
TigerGraph Raises $31M in Series A Funding
TigerGraph, a Redwood City, CA-based provider of a graph database platform for enterprise applications, secured $31M in Series A funding.
Led by Yu Xu, founder and CEO, TigerGraph provides a native complete, distributed and parallel graph database platform for enterprise applications, which powers real-time deep link analytics for enterprises with complex and colossal amounts of data, a cloud service and GraphStudio, a visual software development kit (SDK) designed for technical and non-technical users to create, explore and query graphs visually.
TigerGraph, a graph database born to roar
Imagine your database of choice blown out of the water by a startup emerging from stealth. TigerGraph may have done just that for graph databases.
TigerGraph positions itself as a solution for real-time graph analytics for extremely big data. For doing things such as fraud prevention, recommendations and network management for clients like Alipay, Visa, Wish and the State Grid Corporation of China.
Axios Pro Rata
TigerGraph, a Redwood City, Calif.-based real-time graph analytics platform, has raised $31 million in Series A funding from Qiming VC, Baidu, Ant Financial, AME Cloud, Morado Ventures, Zod Nazem, Danhua Capital and DCVC.
BRIEF-TigerGraph emerges with $31 mln in Series A funding
TigerGraph emerges with $31 mln in Series A funding, introduces real-time graph platform
TigerGraph – series A funding with investors including Qiming VC, Baidu, Ant Financial, AME Cloud, Morado Ventures, Zod Nazem, Danhua Capital, DCVC
BRIEF: TigerGraph Emerges With $31M in Series A funding
TigerGraph emerges with $31 mln in Series A funding, introduces real-time graph platform
TigerGraph – series A funding with investors including Qiming VC, Baidu, Ant Financial, AME Cloud, Morado Ventures, Zod Nazem, Danhua Capital, DCVC
TigerGraph nabs $31 mln Series A
TigerGraph today made announcements including its emergence from stealth, securing of $31M in Series A funding, general availability of TigerGraph – the world’s first and only native parallel graph database platform for enterprise applications, and 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.
The NewStack: Introducing TigerGraph, a Native Parallel Graph Database
While graph technology offers clear competitive advantages, these current solutions are not without their limitations. The most critical of which is the inability to support real-time analytics — a sore point given that enterprise data is always growing and becoming more complex. This is because solutions thus far have been either storage or compute-focused, feature-limited analytics capabilities and are unable to update graphs in real time.
As the world’s first Native Parallel Graph (NPG) database, TigerGraph sets out to solve these challenges. Unlike other technologies, the TigerGraph NPG focuses on both storage and computation, supporting real-time graph updates and offering built-in parallel computation. NPGs represent what’s next in the graph database evolution: a complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time.