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We develop solutions on world’s fastest and most scalable graph platform

Speed

Massively parallel processing provides sub-second response for queries with tens of millions of entities/relationships.

Scale-Out

Scales out with your growing needs (and stays fast, of course). Trillion-edge graphs are running real-time analytics in production.

Graph Analytics

Gain deeper insights through queries which can traverse 10 or more hops and perform complex analytics.

Graph Query Language

The GSQL query language is the choice for high-performance graph operations and analytics. High-level syntax, Turing completeness, and built-in parallelism mean faster performance and development.

Multi-Graph

Multiple groups can share the same master database, while retaining local control and security. This helps enterprises break down data silos, improving transparency and access to data.

Visual Interface

TigerGraph GraphStudio™ is our simple yet powerful graphical user interface. GraphStudio integrates all the phases of graph data analytics into one easy-to-use graphical user interface.


Orbifold B.V.
Leuven, Belgium (Europe)
info@orbifold.net
orbifold.net

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14 hours ago
Visualize big networks within seconds with Cosmograph. Halfway art and science, uses your GPU to speed up force-directed layout. With timeline and graph analytic filtering. And yes, open source. https://t.co/NfTrbKSsgj #Graphs #DataViz https://t.co/Y2jdU6Zx9S
14 days ago
Codon by @exaloop , a high-performance Python compiler that compiles to native machine code without any runtime overhead. Speedups are on the order of 10-100xor more, on a single thread. Codon's performance is typically on par with that of C/C++. https://t.co/g00nZsyR64 #python https://t.co/KbeSpO8IYw
15 days ago
Trillion edges benchmark: new world record beyond 100TB by @TigerGraphDB featuring AMD based Amazon EC2 instances. https://t.co/65sp9zkwPY #GraphDatabase https://t.co/d9BVCsOzem
18 days ago
Watch this space for an updated PowerBI widget based on @yworks. In 5 years since v1 it's easier to create and more powerful (Power Apps, Python & R integration...). Developing graph visualization in @MSPowerBI is so much easier and more fun than Tableau. https://t.co/XOQvZc9FbH https://t.co/iQ0I6n7EOi
18 days ago
The graph of primes exhibits some striking patterns and anomalies, both topologically and in its centrality measures.Can #GraphMachineLearning help here? Based on research with Soumya Jyoti Banerjee https://t.co/MyHBXCcfk6 #graphs https://t.co/RKpVtkGGgs
24 days ago
It takes now less than 100 lines of code to talk to your Neo4j graph (see attached gist). This works with any database really. I used a large biomed graph but this is also arbitrary. Uses GPT3, not ChatGPT. https://t.co/vBeGneS0FO @neo4j #graphs #NLU https://t.co/WTuh8qt81r
28 days ago
JanusGraph, a Gremlin-first #GraphDatabase has a Cypher-for-Gremlin adapter enabling property #Graphs. @TSawyerSoftware has explicit visualization/analytics support. Also check the @Linkurious Ogma dataviz https://t.co/qWF36TbbSp https://t.co/qJYhhnsk93 https://t.co/cwTXhpl8u0 https://t.co/GSkeANqPCC
29 days ago
Here's the real reason why graphs are everywhere. Category Theory is the maths of mathematics and it effectively embodies the idea that #graphs can describe anything and everything. The Wolfram stack excels in this sorta stuff. @WolframResearch https://t.co/UG8rQZlQu4 https://t.co/gLpZeDlIxA
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