Leading research company Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025. If you’re new to graph and wondering what it can do for your ...

Artificial intelligence usage is outpacing internet growth, creating electricity demands that require data centers to consume ...

In contrast, graph databases are designed to handle complex, interconnected questions more efficiently. They can traverse the data and relationships between customers, purchase history, location ...

With the ever increasing explosion in data for analysis and the need for fast insights on emerging trends, in-memory data grids (IMDGs) offer a highly attractive platform for hosting map/reduce ...

Network graphs can show how your customers are segmented and the risk of churn for each segment. You can discover that what you thought were three or four main segments are actually 10.

Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

SHACL allows a data graph, for instance, to specify the corresponding shapes graph used to describe the link between a given shape and targeted data. Franz claims its upgraded, flexible architecture ...

The graph data models are depicted in edge-and-node maps that look less like the nested tables of enterprise RDBMS schemas and more like the corkboard investigation maps of TV crime shows.

As data complexity continues to grow and the demand for real-time insights increases, the move away from traditional relational databases and towards the adoption of graph databases will become vital.