Graph Data Science Consulting
  • Graph Machine Learning
  • Graph Databases
    • Neo4j
    • TigerGraph
  • Graph Visualization
    • yFiles Consulting
    • Linkurious Consulting
    • Go.js Consulting
  • Graph Analytics
  • Articles
  • Contact
  • Search
  • Menu Menu
  • Twitter
  • Facebook
  • LinkedIn

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

Twitter
Facebook
LinkedIn
  • Contact
  • Graph Analytics
  • Graph Visualization Consulting
  • Graph Databases
  • Graph Machine Learning Consulting
  • Articles
16 days ago
Beyond message passing, a physics-inspired paradigm for graph neural networks. https://t.co/viPTHXaPo4 #GraphMachineLearning https://t.co/BKqGJom5pz
74 days ago
Leo Meyerovich from @Graphistry on how and why the best companies are adopting Graph Visual Analytics, Graph AI, and Graph Neural Networks. https://t.co/GQNiKH9EJ4
#GraphAnalytics #GraphMachineLearning https://t.co/g3YYh8UcT2
77 days ago
TigerGraph Machine Learning Workbench is in preview and comes with a custom Jupyter Lab, plus lots of goodies to hook up your favorite graph ML framework. Exciting times ahead. @TigerGraphDB https://t.co/68Xe35GPOt #GraphMachineLearning https://t.co/2Lz0w5NuTm
87 days ago
My article on drug repurposing is now also published on the @TigerGraphDB blog. Thanks to the great Tigers and @CayleyWetzig in particular. https://t.co/uMV1aTvUrr
#healthcare #GraphMachineLearning #KnowledgeGraph https://t.co/inQbftYJGX
99 days ago
If you want to explore the knowledge graph visually in my latest article there is, besides yFiles (https://t.co/QR6wmzOJNS), also @Graphistry (https://t.co/IdqMN7NiNO) which manages to handle very large graphs in the blink of an eye.
#GraphVisualization
https://t.co/RzudOW7DKu https://t.co/CoDtw7RkAQ
100 days ago
Drug Repurposing Using TigerGraph & Graph Machine Learning. https://t.co/MdriWAJzJr #GraphAnalytics #KnowledgeGraphs
https://t.co/QuE2AoYAyk https://t.co/gGNlCQselk
107 days ago
All paths lead to one. A Collatz graph visualization with 1.5 million nodes doesn't prove anything but certainly supports the conjecture. Layout based on custom Wolfram code. #GraphAnalytics
https://t.co/TBqkHzkp6U https://t.co/2WriphA2R4
© 2000-2021 Copyright - Orbifold Consulting | Terms and Conditions | Privacy Policy
  • Twitter
  • Facebook
  • LinkedIn
Scroll to top