TigerGraph positions itself as a solution for real-time graph analytics for extremely big data.

Faster data loading to build graphs quickly Faster execution of parallel graph algorithms Real-time capability for streaming updates and inserts using REST Ability to unify real-time analytics ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at ...

Companies in virtually every industry, from healthcare to energy to financial services, are applying the power of graph analytics to gain real-time insights and answer critical business questions ...

Here, we look at the importance of real-time data to any organization and explore different use-cases and examples that illustrate my real-time data matters more than ever.

Diffbot’s AI model leverages this resource by querying the graph in real time to retrieve information, rather than relying on static knowledge encoded in its training data.

We have seen how Apache Spark can be used for processing batch (Spark Core) as well as real-time data (Spark Streaming). Sometimes the data we need to deal with is connected in nature. For example ...

Real-time indexing on TRON pairs one of the industry’s largest transaction flows with The Graph’s fastest data pipeline, a combination likely to attract new analytics tools, market activity ...