TigerGraph Releases New Benchmark Report – First Time a Graph Database Tested at this Scale

Graph analytics leader TigerGraph has released a new benchmark report which demonstrates the technology is capable of running BI queries fast, returning results in a few minutes or less even across a data set of significant size.

Video Highlights: Emil Eifrem on the Origins of Neo4j and the Ubiquity of Graphs

The video below is from a webinar for Neo4j’s APAC Quarterly Customer Update. It includes a fascinating conversation between Emil Eifrem, Co-Founder and CEO, and Nik Vora, the Vice President of Neo4j APAC.

TigerGraph Unveils Free TigerGraph Enterprise Edition, Helping Companies Use Graph as the Foundation of Many Modern Data, Analytics and AI Capabilities

TigerGraph, the scalable graph database for the enterprise, announced free licenses for TigerGraph Enterprise, an offering that will empower customers to easily use graph analytics and algorithms that quickly traverse graphs to find insights in real-time. TigerGraph is now free for everyone to use for databases up to 50GB graph size (which can be more than 150GB in other graph systems, which expand data rather than compress it).

Graph Analysis Help for COVID-19 Tracking and Research Efforts

TigerGraph is providing technology assistance to those working to track, analyze and research COVID-19. The company is providing free use of TigerGraph’s graph database technology to those helping to prevent the spread of, and improve the treatment for, Coronavirus worldwide. Local, state and federal agencies, corporate users, as well as non-profits can access the free tier on TigerGraph Cloud to load data and perform advanced analysis using graph algorithms.

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.