One of the biggest differences between graph databases and relational databases is that the connections between nodes directly link in such a way that relating data becomes a simple matter of ...

A new semantic-based graph data model has emerged within the enterprise. This data model has all of the advantages of the relational data model, but goes even further in providing for more ...

Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder ...

Graph databases are inherently more flexible than traditional relational database systems because it is possible to treat the metadata about the database as data itself, accessible in exactly the ...

The data management landscape is undergoing a serious transformation. While traditional relational databases have been the “go-to” data storage tool for some time, their limitations in ...

Graph databases have nothing to do with graphics. The reference is to an abstract data type with multiple nodes that can be connected in many ways. Graph structures aren’t relational but aren ...

This adaptability and efficiency in handling relational data make graph databases a pivotal component in modern data analytics and business intelligence strategies. Jump to: The primary function ...

Although it’s still a relational database at its core, it’s based on an object-oriented data model with a strict graph schema and modern query language to ensure ease of use. As the company ...

For sure, RDF/graph databases are not ubiquitous like relational systems, which still dominate the market. Probably the main reason is better predictability in working with lower data abstraction ...