TigerGraph Blog
Harnessing the Potential of Graph AI: Insights from a Marketer’s Perspective
In the ever-evolving landscape of technology, certain innovations emerge that have the potential to shape the future. One such innovation is the emergence of graph
TigerGraph Puts State-of-the-Art Graph Neural Networks within Reach
In a relatively short time, machine learning has completely transformed almost every facet of technology in the business world and in our day-to-day lives. From
What Are the Major Advantages of Using a Graph Database?
A graph database is a data management system software. The building blocks are vertices and edges. To put it in a more familiar context, a
Sink Your Teeth Into FIBO with A Native Parallel Graph Database
Authored by TigerGraph Solutions and Engineering Financial institutions have massive volumes of highly interconnected and structured data, which they need to ingest in real time
Leveraging Geospatial Data with a Native Parallel Graph Database
Paradigm Shift Enables TigerGraph to Uncover Hidden Insights from Geolocation Data Have you wondered how you can add and leverage geospatial data to your applications?
Introducing TigerGraph Cloud: The Fastest and Most Complete Graph Database-As-A-Service for Everyone
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
Building a Graph Database on a Key-Value Store?
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
Crossing the Chasm – Eight Prerequisites For A Graph Query Language
Prelude In December, I wrote a Quora post on the pros and cons of graph databases. I shared two cons pervasive in the market today:
