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Graph Analytics Expands to the Cloud

Graph continues to be the fastest growing segment of data management. The benefit: the ability to offer deeper insights on data and in real-time, therefore enabling better business outcomes. A number of graph solution providers are continuing to innovate by taking their technology to the cloud. Specifically, we’re seeing enterprise-class, Pay-As-You-Go graph analytics solutions in the cloud based on Amazon Web Services.

Expanding Adoption for Graph Databases

In order to facilitate access to graph database technology Neo4j, a leader in graph databases, announced that it has expanded the availability of its free Startup Program. Neo4j graph technology drives innovation at NASA, eBay, Airbnb, and Adobe. The Neo4j Startup Program ensures the next generation of world-changing startups are powered by the leading graph database technology.

TigerGraph Cloud: the Fast and Complete Graph Database-as-a-Service for Everyone

TigerGraph, the fast graph analytics platform for the enterprise, introduced TigerGraph Cloud, the simplest, most robust and cost effective way to run scalable graph analytics in the cloud. Users can easily get their TigerGraph service up and running, tapping into TigerGraph’s library of customizable graph algorithms to support key use cases including AI and Machine Learning.

Interview: Dr. Yu Xu, CEO and Founder of TigerGraph

I recently caught up with Dr. Yu Xu, CEO and Founder of TigerGraph, to discuss the genesis of graph analytics, how the technology has evolved over time, how it’s being used today, along with a sense for where the graph market is headed.

TigerGraph Adds Role-Based Security to Its Enterprise-Ready Graph Database Platform

TigerGraph, creator of the native parallel graph database platform for enterprise applications, announced the addition of role- and view-based security to its Native Parallel Graph (NPG) platform. The new feature delivers enhanced security, enabling enterprises to create and administer access to subgraphs on a single cluster for controlled data access.

Apache Spark Expands With Cypher, Neo4j’s ‘SQL For Graphs,’ Adds Declarative Graph Querying

Neo4j, a leader in connected data, announced that it has released the preview version of Cypher for Apache Spark (CAPS) language toolkit. This combination allows big data analysts to incorporate graphs and graph algorithms in their work, which will dramatically broaden how they reveal connections in their data.

The State of Graph Databases – Worldwide Adoption and Use Case Characteristics

A new paper, “The State of Graph Databases – Worldwide Adoption and Use Case Characteristics,” provides an overview of graph technology, details the results of a new IBM survey—and highlights findings that debunk some of the most popularly held views about graph technology.

The State of Graph Databases – Worldwide Adoption and Use Case Characteristics

This paper provides an overview of graph technology, details the results of the survey conducted by IBM, in partnership with TechValidate, of 1,365 entrepreneurs and developers about the potential they see for graph databases as well as their current and planned use for this technology—and highlights findings that debunk some of the most popularly held views about graph technology.

Cross-Channel Advertising with Large-Scale Consumer Graphs

In this contributed article, Deb Ray, Chief Data Officer at VideoAmp discusses an important technique where the complexity of cross-channel targeting and measurement is solved by building a large-scale graph of consumers and their connected devices.

Introducing Neo4j 3.1: The Graph Foundation for the Enterprise

Neo Technology, creator of Neo4j, the world’s leading graph database, announced the release of Neo4j 3.1, a major release with new operational and security features that make it easier to deploy Neo4j broadly across an entire enterprise.