Building a Next Level Intelligent RASA Chatbot with TigerGraph
Did you know how easy it is to create a conversational assistant? With machine learning/Artificial intelligence. Building a powerful chatbot Assistant has always been a
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
TigerGraph Proves to be a Special Resource for High School Students in Hackathon
The Randomness of Opportunities Hackathons can be stressful experiences, as a group of students from Eden Prairie, Minnesota recently found out. The students, belonging to
It’s Official: We’re On the Road to a Standardized Graph Query Language
Last week I attended my third face-to-face meeting for WG3, a subgroup of ISO/IEC Joint Technical Committee 1 (JTC1), and the group that has developed,
The Good News Keeps On Coming – Introducing TigerGraph Cloud & Announcing TigerGraph Series B
We’re delighted to share news about two very exciting developments. The first is the launch of our graph database-as-a-service with a free tier for no-risk
‘+=’ As The Key That Unlocks The Power of the Network
My job as a TigerGraph SE is to help a prospective customer solve their problems using our product. We are unusually successful, even though we
New Query Language for Graph Databases to Become International Standard: GQL
We’re thrilled to see this big step forward for the Graph Query Language (GQL) team, as the key international standards body (ISO/IEC JTC 1) has
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
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
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
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
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
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
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: