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 ...

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 ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now The graph database stands as one of the ...

As enterprises continue to navigate the complexities of digital transformation, connected data is becoming an increasingly common necessity. Connected data is when data assets are linked together to ...

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 ...

Keyword search in graphs and relational databases constitutes a pivotal research domain that seeks to bridge the gap between natural language queries and complex data repositories. By enabling users ...

A new generation of graph databases has taken hold, and a generation of query languages has arrived alongside them. The assorted graph database query languages include the likes of Gremlin, Cypher, ...

The cloud has been a boon for enterprises trying to manage the massive amounts of data they collect every year. Cloud providers don’t have the same scaling issues that dog on-premises environments.

It’s not exactly clear where we are in the Gartner Hype Cycle with respect to so-called “NoSQL” databases. We’ve definitely been through the Trough of Disillusionment, but are we in the Slope of ...

Data scientists, engineers and managers having been working for the past 50 years at methodologies to gain better business insights from large stores of data. Despite advances in cloud data storage ...