Introducing The Latest Release Of TigerGraph: Fastest Performance For Graph Analytics

By AIT News Desk On Sep 19, 2018

Newest Release Features Expanded Toolset, Helping Enterprises Accelerate Time to Value with Graph Analytics

TigerGraph, the world’s fastest graph analytics platform for the enterprise, introduces its latest release, designed to help enterprises harness the power of the fastest and most scalable graph analytics more easily than ever before. New features include seamless integration with popular databases and storage systems, support for Docker and Kubernetes containers, availability on the Amazon Web Services Marketplace and Microsoft Azure, and a new graph algorithm library. TigerGraph additionally unveiled its eBook, “Native Parallel Graph: The Next Generation of Graph Database for Real-Time Deep Link Analytics.”

“TigerGraph offers superior performance that’s proven – particularly with speed and scalability compared to first generation graph database solutions like Neo4j,” said Dr. Yu Xu, CEO and founder, TigerGraph. “Organizations already rely on TigerGraph to enable some of the world’s largest and most mission-critical use cases. Today’s release makes it even easier for enterprises to connect TigerGraph to their existing infrastructure. It’s all part of our commitment of delivering the best graph engine on the market to power the applications that are paving the way of the future.”

TigerGraph enables organizations to accelerate their time to value to gain maximum insight from massive amounts of interconnected data at lightning speed. With accelerated scale out capability and TigerGraph’s novel MPP implementation, TigerGraph provides the perfect fit for organizations to quickly adapt to the data needs of the future.

Key New TigerGraph features include:

Frictionless integration with popular databases and data storage systems including: RDBMS, Kafka, Amazon S3, HDFS, and Spark (coming soon). A new TigerGraph EcoSys GitHub repository will now host open source connectors to TigerGraph as they roll out.

Expanded deployment options that enable users to implement a performant and scalable graph as they wish, in a cloud-neutral environment. TigerGraph supports one-click install for major cloud marketplaces – such as Amazon AWS Marketplace and Microsoft Azure – helping customers control where their data is stored to prevent cloud vendor lock-in. TigerGraph also offers new support for Docker and Kubernetes containers for easy portability across on-premise and cloud environments.

Graph algorithm library containing efficient GSQL implementations of popular graph analytics functions such as PageRank, Shortest Path, Connected Components and Community Detection. Leveraging TigerGraph’s MPP performance and the expressiveness of GSQL, TigerGraph is delivering its high-performance library as a user-extensible set of GSQL queries, the same queries used in its recent benchmark report.

Developer resources, including a new eBook, “Native Parallel Graph: The Next Generation of Graph Database for Real-Time Deep Link Analytics.” The eBook discusses what developers need to learn to leverage the power of scalable and MPP graph analytics for the most complex business problems.

Today, companies demand real-time data insight to make informed decisions and to provide better customer experiences. Graph analytics are optimized to deliver new insight and intelligence previously impossible or hard to detect, allowing enterprises to capture key business moments for competitive advantage.

TigerGraph offers the world’s fastest graph analytics platform that tackles the toughest data challenges in real time, no matter how large or complex the data set. TigerGraph stores all data sources in a single, unified multiple-graph store that can scale up and out easily and efficiently to explore, discover and predict relationships. Unlike traditional graph databases, TigerGraph can scale for real-time multi-hop queries spanning trillions of relationships.