One of the great things about the database market is that there are many different kinds of data and the problems that need to be addressed to store, organize, and query that data are also increasing ...

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 ...

Data Visualization is a widely used technique for visualizing, analyzing, and presenting datasets using different types of graphs. It is an effective way to evaluate a large data set using pictorial ...

Graph databases, such as Neo4j, Apache Spark GraphX, DataStax Enterprise Graph, IBM Graph, JanusGraph, TigerGraph, AnzoGraph, the graph portion of Azure Cosmos DB, and the subject of this review, ...

Graph processing at hyperscale has historically been a challenge because of the sheer complexity of algorithms and graph workflows. Alibaba has been tackling this issue via a project called GraphScope ...