Graph analysis will push big data evolution to the next plateau of scale and sophistication. Hadoop is one segment of the evolutionary picture, but it’s not necessarily the centerpiece.

Developers writing graph applications that scale into the billions of vertices and trillions and edges are forced to make trade-offs that impact the performance of the application. But thanks to new ...

The prevalence of big data and the value it generates has greatly, and perhaps indelibly, altered contemporary business practices in two pivotal ways. Firstly, the value of just-in-time analytics is ...

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.

While privacy advocates have expressed concern about the phenomenon of massive data collection and analytics colloquially known as “big data,” most people are more familiar with social media ...

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.

Facebook's engineers have many challenges ahead of them as they work to scale up Graph Search, the site's new social search tool. One stumbling block: an over-abundance of data to sift through.

Graph data meets GIS maps. Connecting graph representations of data with geographic data has particular value in many applications, according to Jean Villedieu, cofounder and managing director ...

Apache Spark: Best for open-source big data processing. ... Supports SQL analytics, streaming data, machine learning and graph processing. Data science on petabyte-scale data.