Improve Profitability with AWS and TigerGraph

TigerGraph provides fast and scalable graph analytics of big data, enabling Amazon Web Services (AWS) customers to uncover insights and leverage connected data in enterprise applications in financial services, e-commerce, manufacturing, healthcare. and more. TigerGraph Cloud uses the robust and secure AWS infrastructure to power its scalable graph database-as-a-service. 

TigerGraph Cloud on AWS

TigerGraph Cloud is one of the only distributed and scalable graph database-as-a-service offerings on AWS Marketplace. Data scientists, business analysts and developers can get started with TigerGraph Cloud, an easy-to-use, fully managed as a Service, cloud-based graph database built for agile teams.


TigerGraph Cloud uses various AWS services as the Infrastructure backend to provide customers with a database-as-a-service offering, where AWS infrastructure and TigerGraph services are fully provisioned, managed and maintained.

Listen to Vikram Vunduru, Partner Engineer at AWS, and Shuo Yang, Head of Cloud at TigerGraph, present how AWS and TigerGraph work together to provide the scalable distributed graph database-as-a-service, based on AWS. The session goes over our high-level architecture and a demo of TigerGraph cloud portal. In high level, a universal controller is used to integrate with Terraform templates to provision and control the full TigerGraph stack in AWS. 


Companies leverage the power of TigerGraph Cloud on AWS for many key applications, including: Anti-money laundering, Customer 360, Cybersecurity, Entity Resolution, Fraud Detection, Machine Learning, Personalized Recommendation Engines, and Supply Chain.  TigerGraph supports organizations with Cloud for Marketing Analytics, Application Modernization, Database Modernization and Artificial Intelligence business initiatives.

Just a few of the customers using Tigergraph Cloud on AWS to analyze large amounts of data in real-time and make decisions that positively impact their bottom line, include:

  • Intuit’s fraud detection model detected 50% more risk events and improved prediction accuracy by 50%, using machine learning, visualization, and TigerGraph.
  • Kickdynamic helps their customers–such as luxury clothing retailers–deliver real-time targeted recommendations, resulting in increased engagement, brand loyalty, and sales conversions while helping marketers to streamline their internal manual email build processes.
  • Wish became the 3rd-largest eCommerce platform in the United States in under 10 years with more personalized and effective recommendations powered by TigerGraph. 

Achieve even more when you combine TigerGraph Cloud with SageMaker, RedShift, and other AWS solutions. Everyone, from data scientists to business users, can get started with TigerGraph Cloud and AWS, in minutes, not hours. Start today.