TigerGraph Delivers Graph to All with Latest Cloud Offering; New Visualization and Machine Learning Features Simplify Graph Technology Adoption for Deeper Business Insights

Latest Cloud Capabilities Empower Developers, Data Analysts, and Data Scientists to Tap into the Power of TigerGraph’s High-Performance, Scalable Platform with Simple, Intuitive Tools

TigerGraph, provider of the leading advanced analytics and ML platform for connected data, announced the latest version of TigerGraph Cloud, the industry’s first and only native parallel graph database-as-a-service, highlighted by two powerful new tools for visual graph analytics and machine learning. TigerGraph Insights, an intuitive visual graph analytics tool for users to search and explore meaningful business insights, and ML Workbench, a powerful Python-based framework to accelerate the development of graph-enhanced machine learning applications, are available today to TigerGraph Cloud users.

“TigerGraph has long been committed to both democratizing graph and pushing the limits of industry innovation. Our latest release of TigerGraph Cloud does both, helping developers and data scientists unlock the full potential of their data,” said Jay Yu, vice president of product and innovation at TigerGraph. “The addition of visual graph analytics and machine learning tools to our fully managed graph database-as-a-service offering — which is available on all major cloud platforms — lowers the barrier to graph entry even further. Now, enterprises of all sizes can supercharge their data analytics and machine learning projects at scale with speed, asking and answering critical business questions that move the needle.”

TigerGraph Cloud is the industry’s first and only distributed native graph database-as-a-service, enabling users to accelerate the adoption of graph technology with easy-to-use features that process analytics and transactional workloads in real time. Available on Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure, TigerGraph Cloud now equips users with a comprehensive, streamlined approach to deploy and maintain multiple graph database solutions with visual analytics and machine learning tools. ​​The latest version of TigerGraph Cloud gives customers better predictions with data they already have, what-if analyses with a no-code approach, and out-of-the-box support for new ML graph feature engineering.

TigerGraph Insightsis a no-code and low-code visual graph analytics tool that enables both technical and non-technical users to create compelling, interactive visual representations of business intelligence applications on top of TigerGraph’s massive parallel graph database platform. The Insights tool connects intuitive graph data with traditional business intelligence to produce multidimensional and interactive graphics. These graphics can be linked together to produce compelling tables, charts, and maps that visualize graph stories. Graphics can also be connected within an interactive dashboard application for easy sharing to gain deeper understanding and insight into connected data. Insights, with its no-code development for deep graph analytics and insights, offers customers easy point-and-click, drag-and-drop visual interfaces as well as progressive visual graph pattern search, dynamic linkage, and navigation.

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Meanwhile, TigerGraph’s ML Workbench is a powerful graph machine learning toolkit that empowers data scientists to significantly improve ML model accuracy, shorten development cycles, and deliver more business value. Users can do all of this while using familiar tools, workflows, and libraries in a single environment that easily plugs into existing data pipelines and ML infrastructure. Data scientists can seamlessly launch built-in high-performance graph feature generation, sampling, and training powered by TigerGraph’s massive parallel graph data compute engine and 55+ open source graph algorithms. The resulting graph features are extracted and converted into efficient data formats required by downstream graph neural network modeling. ML Workbench offers a seamless plugin to data science workflows — and it is directly embedded in the most popular data science toolkit (Jupyter Notebook).

TigerGraph Cloud, with the addition of TigerGraph Insights and the ML Workbench, now offers a comprehensive set of tools that is easily accessible via TigerGraph Suite, a single streamlined portal that enables frictionless collaboration among graph users. These users can easily switch between the following tools with the click of a button:

  • GraphStudio: Visual development tool for graph database developers
  • GSQL Shell: Command line tool for graph query developers
  • GraphQL Gateway: Service integration tool for application developers
  • AdminPortal: User management, system administration, and monitoring for DevOps
  • Insights: Visual graph analytics tool for data analysts and non-technical users
  • ML Workbench: Graph machine learning tool for data scientists

TigerGraph Cloud users can choose from 20+ starter kits that cover real-world industry use cases such as customer 360, fraud detection, supply chain analysis, cybersecurity, and more. Starter kits are pre-built with sample graph data schema, dataset, and queries focused on specific use cases such as fraud detection, real-time recommendation, machine learning, explainable AI, and more.

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