Temporal database systems are designed to capture and manage data that varies over time, thereby accommodating historical and time‐sensitive information. These systems integrate temporal dimensions ...

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 ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

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 ...

Douglas Adams once wrote of a Holistic Detective Agency. The central character in this story, Dirk Gently, was able to solve cases with his understanding of the fundamental interconnectedness of ...

Sure, there are graph databases like Neo4j, but graph analysis or graph search may be more useful, depending on the sorts of data relationships you need to explore Graph processing is hot right now in ...

DataStax Inc. is hoping to jump-start graph databases out of their niche with a real-time graph engine targeted at cloud applications that manage high-volume changeable data. The company is today ...

Perhaps the most important decision that any company will ever make is how they intend to structure and store the information they will preserve to encapsulate the goods and services they provide to ...

In this special guest feature, Emil Eifrem, Founder and CEO of Neo Technology suggests that in order to achieve connected enterprise status and realize the significance of the graph database, ...