Every decade seems to have its database. During the 1990s, the relational database became the principal data environment, its ease of use and tabular arrangement making it a natural for the growing ...

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 ...

Graph databases are gaining attention as enterprises work on their next-generation artificial intelligence (AI) applications. While still a bit of an outlier, graph-oriented databases continue to find ...

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 ...

Graph databases are the fastest growing database technology, representing a departure from the relational and NoSQL models – a departure that is inherently worthwhile. Graph Databases For Dummies, ...

eWeek content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More Graph databases are now clearly riding the upward trend ...

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, ...

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 databases, which explicitly express the connections between nodes, are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. That ...

Twenty years ago, my development team built a natural language processing engine that scanned employment, auto, and real estate advertisements for searchable categories. I knew that we had a difficult ...