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 ...

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 ...

In the quest to teach software to understand language, scientists have mainly focused on text as a source of data to help train their algorithms. Among other things, text is used to populate a ...

In the age when data is everything to a business, managers and analysts alike are looking to emerging forms of databases to paint a clear picture of how data is delivering to their businesses. The ...

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 ...

Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it makes ...