Natural language processing techniques are used to extract entities and relationships from data, such as text documents, and populate the graph with information from various sources is essential.

A new open-source library by Nvidia could be the secret ingredient to advancing analytics and making graph databases faster. The key: parallel processing on Nvidia GPUs.

The end result is a dramatic increase in performance of graph applications, according to the researchers. To prove it, the researchers ran GraphIt against six other shared-memory graph frameworks, ...

Spanner Graph, according to Steven Dickens, chief technology advisor at The Futurum Group, will address the increasing demand for advanced data processing and analytics solutions in various ...

Graph analytics can be performed on any back end, as they only require reading graph-shaped data. Graph databases are databases with the ability to fully support both read and write, utilizing a ...

Learn More Katana Graph, a startup that helps businesses analyze and manage unstructured data at scale, today announced a $28.5 million series A round led by Intel Capital.

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 ...

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 ...