For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of large AI models, integration with graph databases is now required. This process ...

RelationalAI has long believed that a shared, open language for business and domain semantics is essential for trustworthy, intelligent applications,” said Molham Aref, CEO of RelationalAI. “Today, ...

Microsoft Fabric expands as industry analysts reveal critical criteria enterprises need for evaluating AI-ready data ...

Wouldn’t it be funny if Larry Ellison, who has become the elder statesman of the datacenter, had the last laugh on the cloud ...

Even though traditional databases now support vector types, vector-native databases have the edge for AI development. Here’s ...

MongoDB Inc. is expanding beyond its database roots and taking aim at one of the thorniest challenges facing many enterprise ...

If the hyperscalers are masters of anything, it is driving scale up and driving costs down so that a new type of information ...

AI's shift to inference at scale from model development is tilting data-center demand toward databases, especially those used ...

This does not prevent us from starting to use the technology early in its development, as was the case with relational ...

Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, ...