1. Problem Description Enterprises know the benefits of merging data from multiple sources, to build more detailed and more complete records about their customers, their products, their employees, etc. The sources may be different departments or computer systems within one enterprise, a combination of internal and...
Today we are proud to introduce TigerGraph Cloud, the simplest, most robust and cost effective way to run scalable graph analytics in the cloud. As graph continues to cross the chasm, more and more organizations seek to get value from graph as quickly as possible....
It’s that time of the year when 40,000+ people cram into Las Vegas for Amazon AWS re:Invent , which kicks off November 26. If you think about it, the attendees are all connected, but don’t realize it. It’s like a huge graph and many new insights and...
Recently RedisGraph published a blog [1], comparing their performance to that of TigerGraph's, following the tests [2] in TigerGraph's benchmark report [3], which requires solid performance on 3-hop, 6-hop, and even 10-hop queries. Multi-hop queries on large data sets are the future of graph analytics. After...
by Dr. Xu Yu, CEO and Dr. Victor Lee, Director of Product Management [Excerpted from the eBook Native Parallel Graphs: The Next Generation of Graph Database for Real-Time Deep Link Analytics] Until recently, graph database designs fulfilled some but not all of the graph analytics needs of...
Graph databases and analytics have crossed the chasm - and the data supports it. Take, for example, how graph databases are the fastest growing category in all of data management (according to DB-Engines.com). Survey data further shows that more than 40 percent of organizations currently...
With the graph database market on the rise, it is important to understand the differentiators between each vendor. TigerGraph is the first and only native parallel graph with massively parallel processing, but does that translate into the fastest performance? We're happy to report: yes. With TigerGraph’s...
What a difference a year makes. One year ago, we presented the public launch of TigerGraph 1.0, delivering the next stage in the evolution of graph database with the world’s fastest and most scalable graph platform. This came after five years in stealth developing state-of-the-art technology...
In May this year, Amazon announced the General Availability of its cloud graph database service called Amazon Neptune. Here is a comprehensive blog that summarizes its strengths and weaknesses. Last year, we published a benchmark report on Neo4j, Titan and TigerGraph. It is intriguing for...
This month we kicked off Graph Gurus, our webinar series for developers who are looking to address real-world problems with graph database technology and graph analytics. Our goal is to make you Graph-Smart, so you can see when a graph could benefit you, and to...
