Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.

Understanding the relationships in graph database theory allows us to work with the new 'shape' of data itself. Businesspeople like graphs. C-suite executives are fond of pie charts, Venn diagrams, ...

Knowledge Graphs are quickly being adopted because they have the advantages of linking and analyzing vast amounts of interconnected data. The promise of graph technology has been there for a decade.

There’s no denying it: Graph databases are hot. According to DB-Engines.com, graph databases have outgrown every other type of database in popularity since 2013, and not by a small margin either. It’s ...

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Most enterprise software has a contingent of zealots, people so steeped in the technology that they are convinced it is the be-all and end-all, or those who have taken so many certification exams that ...

The problem: The app must store a collection of people and who they know. Sometimes it must find out everyone who knows someone who knows Bob. Sometimes it must look further for everyone who is three ...

The big data revolution is generating a mess of unruly data that’s difficult to parse and understand. This is to be expected–explosions don’t generally occur in a nice, orderly fashion, after all. But ...

Ever since the introduction of the Google Knowledge Graph, a growing number of organizations have adopted this powerful technology to drive efficiency and effectiveness in their data management.

Graph databases have always been useful to help find connections across a vast data set, and it turns out that capability is quite handy in artificial intelligence and machine learning too. Today, ...