Graph theory isn’t enough. The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them) — has been an invaluable way ...

Forbes contributors publish independent expert analyses and insights. I write about blockchain and big data, primarily focusing on XRP. By applying a well-known graph algorithm to the XRP ledger ...

Dr. Alin Deutsch of UC San Diego explains in a Q&A why graph database algorithms will become the driving force behind the next generation of AI and machine learning apps.

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.

June 29, 2020 – Nebula Graph is now commercially available as the only database that can store and process billions of data points with trillions of relational connections in a shared-nothing ...

Graph databases’ best applications, he said, appear where query processing across complex networks of relationships is vital. He cites MDM, transport logistics and data lineage as such examples.

In today’s world of big data, learning from the vast amount of information collected every day is critical for the firms that rely on it for manufacturing, marketing, decision-making and more. Often, ...

They know what can and cannot be done with data and how to interpret and visualise data and algorithms to provide information for real impact. At the beginning of this year, UN Global Pulse worked ...

The Graph 500 was created to chart how well the world’s largest computers handle such data intensive workloads. The latest edition of the list was released at the SC12 supercomputing conference ...