Analytical Transaction Processing (ATP): Real-Time, Graph Decision-Making Made Easy
Originally posted on ITProPortal There are two “must have” ingredients to making effective business decisions: a complete contextual view of the situation and real-time data.
User-defined Indexes In TigerGraph 3.0
Introduction User-defined Indexes or Secondary Indexes (as they are commonly called in Database Industry) are a critical feature that enhance the performance of a database
Building the Next-Generation Agile Catalog for Retail eCommerce with Graph Database & Analytics
Introduction Product catalog and inventory management is the foundation and is crucial to the success of any eCommerce or traditional retailer. Selling products through multiple
TigerGraph Cloud – The Scalable Distributed Graph DBaaS Supports Microsoft Azure
When we developed TigerGraph, the scalable graph database as a service for agile teams who’d rather be building innovative applications to deliver new insights than
Improving Route Management with Advanced Analytics Powered by Graph Analytics
Why We Need Route Management Without efficient commodity shipping systems, online shopping can not gain its popularity today. By 2040, long-haul freight shipping by truck in
TigerGraph 2020 Graphathon
You are Invited to Participate! TigerGraph 2020 Graphathon We are excited to extend an invitation for you to participate in the first TigerGraph global event,
Introducing TigerGraph 3.0
This blog is the first in a series to unveil the TigerGraph 3.0 GA release. In this blog, we would like to talk about the
Everything to Know to Pass your TigerGraph Certification Test
Originally posted on Towards Data Science by Shreya Chaudhary. What’s TigerGraph and Why Should I Get Certified? Listed as one of Gartner’s top ten data
Infection Chains: Discovering the Unknown using Graph Analytics
Quick Shoutout to Simon Sinek on his Golden Circle of WHY, HOW, WHAT. To learn more on that framework check Simon out on his website
Data Lakes will Yield More Business Value when Combined with Graph Databases
Although traditional data warehouse environments have been around for years now, scalability and performance have become a challenge in the face of a big data
Implementing a 24-Join SQL Query in a Graph Database
Many people are unaware that some difficult-to-write and inefficient-to-execute SQL queries can be easily expressed and efficiently executed in a graph database. This is true
Using A Graph Database for Big Data Entity Resolution
We’re Being Deluged By Data According to market intelligence company IDC, the “Global Datasphere” in 2018 reached 18 zettabytes. (Yes, that zettabytes!) And the problem
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: