Part I of our series on graph analytics introduced us to graph analytics, and its brethren graph databases. We talked about the use of graph analytics to understand and visualize relationships between ...

Even though graph analytics has not disappeared, especially in the select areas where this is the only efficient way to handle large-scale pattern matching and analysis, the attention has been largely ...

Graph technology has become a requirement for the modern enterprise. Companies in virtually every industry, from healthcare to energy to financial services, are applying the power of graph analytics ...

The field of graph analytics was virtually unknown outside of the academic realm just a few years ago, but all that has changed with the market’s insatiable hunger for all things big data. The top two ...

The latest trends and issues around the use of open source software in the enterprise. As defined nicely here by Hitachi Vantara’s Bill Schmarzo, “Graph analytics leverage graph structures to ...

Neo4j is both the original graph database and the continued leader in the graph database market. Designed to store entities and relationships, and optimized to perform graph operations such as ...

Graph databases highlight relationships among the data elements that are otherwise invisible in a tabular format. Furthermore, the analysis is transformed from a descriptive viewpoint — analytics that ...

How would you feel if you saw demand for your favorite topic — which also happens to be your line of business — grow 1,000% in just two years’ time? Vindicated, overjoyed, and a bit overstretched in ...

With a $9.2 million grant from Intelligence Advanced Research Projects Activity (IARPA), Prof. Andrew A. Chien will lead a team of University of Chicago computer science researchers building the ...

As we've been keeping track of the graph scene for a while now, a couple of things have started becoming apparent. One, graph is here to stay. Two, there's still some way to go to make the benefits of ...