Graph database developer Neo4j Inc. is upping its machine learning game today with a new release of Neo4j for Graph Data Science framework that leverages deep learning and graph convolutional neural ...

If open source is the new normal in enterprise software, then that certainly holds for databases, too. In that line of thinking, Github is where it all happens. So to have been favorited 10.000 times ...

The unprecedented explosion in the amount of information we are generating and collecting, thanks to the arrival of the internet and the always-online society, powers all the incredible advances we ...

Graph databases hold numerous attractions for financial services users, among them the ability to detect hidden patterns in data that could be harder to spot otherwise. Some financial institutions are ...

Data models and query languages are admittedly somewhat dry topics for people who are not in the inner circle of connoisseurs. Although graph data models and query languages are no exception to that ...

Graph data, e.g., social and biological networks, financial transactions, knowledge graphs, and transportation systems are pervasive in the natural world, where nodes are entities with features, and ...

The updated graph database-as-a-service (DBaaS) will come with visual analytics and machine learning tools, made accessible via the TigerGraph Suite. Dubbed TigerGraph Insights, the visual analytics ...

Quantum computers have the potential of outperforming classical computers in some optimization and data processing tasks. However, quantum systems are also more sensitive to noise and thus prone to ...