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…
Hyper-Personalized Recommendation Engine Powered by a Native Parallel Graph
Hyper-Personalized Recommendation Engine Powered by a Native Parallel Graph
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…
TigerGraph 2.4 – Overview and Demo
TigerGraph 2.4 - Overview and Demo