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TigerGraph Brings Pay-As-You-Go Graph Analytics to the Cloud with New Offering on AWS

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According to a new press release, “TigerGraph, the only scalable graph database for the enterprise, is accelerating its cloud strategy with the availability of its platform as a pay-as-you-go offering on Amazon Web Services (AWS). This move broadens the company’s global reach by providing AWS users with instant access to the world’s fastest and most scalable graph database. TigerGraph also announced it has now achieved Advanced Partner Status in the AWS Partner Network (APN). To obtain this status, TigerGraph’s platform passed AWS’ stringent technical certification process. In addition, TigerGraph had to validate its expertise through a wide range of enterprise references that demonstrated strong customer value. TigerGraph’s customers run applications in AWS for some of the largest brands in the world across financial services, healthcare, and retail.”

The release goes on, “With the launch of the pay-as-you-go offering, customers will be able to enjoy a friction-free experience for using TigerGraph’s fast and powerful graph database, without cumbersome acquisition and deployment processes. AWS users can now get an Amazon Machine Image (AMI), which includes the TigerGraph DB and GraphStudio SDK. TigerGraph’s launch in the AWS Marketplace provides an easy-to-use and powerful cloud-based solution with fast deployment and pay-as-you-go pricing. ‘Graph analytics are essential for solving today’s most complex business challenges and for making data-driven decisions. We are bringing to market an easy and affordable way for users to tap into the value of graph, via the cloud,’ said Dr. Yu Xu, CEO and founder of TigerGraph. ‘Achieving Advanced Partner Status in the AWS Partner Network is yet more proof that TigerGraph on the cloud is delivering exceptional time to value for its customers and partners, and providing a pay-as-you-go model on AWS helps put the power of the graph into broadest possible adoption, regardless of whether it’s for a fraud detection use case or recommendation engine, AI or Machine Learning’.”

Read more at Globe Newswire.

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