Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

How do you solve the age-old data integration issue? We addressed this in one of the first articles we wrote for this column back in 2016. It was a time when key terms and trends that dominate today's ...

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

Let G be a directed graph such that every edge e of G is associated with a positive integer, called the index of e. Then G is called a network graph if, at every vertex v of G, the sum of the indices ...

Polyglot persistence is becoming the norm in big data. Gone are the days when relational databases were the one store to rule them all; now the notion of using stores with data models that best align ...