Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around ...

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.

Advantages Offered by Graph Analytics. A key advantage of graphs is the ease with which new sources of data and new relationships can be added. Graph databases using Resource Description Framework ...

Graph analytics databases have been described as embodying the next generation of data storage connected with AI, and that's what innovation is all about: a new-and-improved version of how ...

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 ...

Also: From big data to AI: Where are we now, and what is the road forward? Neo4j is the market leader in graph databases, as per the DB-Engines index.We've had a number of conversations with Emil ...

It depends on the data set, he said. “A graph is a good abstraction for a social network, but social networks are so much more. With higher-order systems, there are more ways to model.” ...

The majority of APIs required are formed on relationships between different types of events or different types of data. Graph databases have been spotlighted as the best way to connect these data ...

To illustrate the kinds of relationship that a hypergraph can tease out of a big data set — and an ordinary graph can’t — Purvine points to a simple example close to home, the world of scientific ...