Just a Key-Value Problem? How Graph Reduces Memory Consumption, Accelerates Performance and Overcomes Problems with Key-Value Databases
Key-value databases have long been used for a variety of applications to provide pre-computed results in real-time. There is, however, an increasing shift towards using Graph technology for real-time applications…
It’s Not Just Hype – Graph is Transforming Businesses
First, the good news. In a recent report, Top 10 Data and Analytics Technology Trends That Will Change Your Business, Gartner Research identified graph database and analytics as a key…
The Power of Graph Technology for Marketing Medicine
Originally featured on The New Stack An oft-quoted study by the Tufts Center for the Study of Drug Development estimates the cost of developing a new drug, from R&D to…
Accumulator 101
Originally featured on DZone Motivation GSQL is a Turing complete Graph Database query language. Compared to other graph query languages, the biggest advantage is its support of Accumulators — global or…
The Beauty of Graph Algorithms with Built-in Parallelism
Many people already know that graph algorithms are the most efficient and sometimes the only solution for complex business use cases, such as clustering different groups of users (Community Detection),…
GSQL For Cypher Users
Originally featured on DZone This article is intended for Neo4j Cypher users who want to learn and understand TigerGraph’s GSQL query language. This is by no means a primer on…
Why Experts See Graph Databases Headed for Mainstream Use
Written by Chris Preimesberger, originally featured in eWeek July 5, 2019 Graph databases are now clearly riding the upward trend toward mainstream adoption for which the sector has been waiting…
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