Part I of our series on graph analytics introduced us to graph analytics, and its brethren graph databases. We talked about the use of graph analytics to understand and visualize relationships between ...

LONDON--(BUSINESS WIRE)--Graph technology and graph analytics are used across industries for different purposes, including social media analysis, risk analysis, fraud detection and prevention, and ...

Graph databases highlight relationships among the data elements that are otherwise invisible in a tabular format. Furthermore, the analysis is transformed from a descriptive viewpoint — analytics that ...

REDWOOD CITY, Calif., March 16, 2020 – TigerGraph, a scalable graph database for the enterprise, unveiled TigerGraph 3.0, which delivers the power of scalable graph database and analytics to everyone ...

COMPANY ANNOUNCEMENT: Serverless offering with 65+ ready-to-use algorithms boosts model accuracy by up to 80% and delivers 2X deeper insights - no graph expertise needed Neo4j, the world’s leading ...

Hadoop has emerged as the go-to platform for sifting through massive amounts of data on commodity machines. But when it comes to certain types of analytic workloads with open-ended problems, nothing ...

As the sources, types, and amounts of data continue to expand, so will the need for different kinds of analytics to make something of that data. Unfortunately, there is not a one-size-fits-all ...

Graph databases such as Neo4j, TigerGraph, Amazon Neptune, the graph portion of Azure Cosmos DB, and AnzoGraph, the subject of this review, offer a natural representation of data that is primarily ...

The uses of graph technology continue to expand and change the way people in all professions can uncover and analyze the relationships between data. I’ve written extensively about graphs in the past ...

The latest trends and issues around the use of open source software in the enterprise. As defined nicely here by Hitachi Vantara’s Bill Schmarzo, “Graph analytics leverage graph structures to ...