4 Advantages to Streaming Analytics in Graph Form

Discover how streaming analytics in graph form revolutionizes data analysis, offering instant insights, deep relationships, and categorical data analysis.

Graph Neural Networks for Quine

Quine 1.5 includes support for graph neural network techniques like Node2Vec and GraphSAGE. This post provides an overview and tutorial.

Categorical Data: An Untapped Source of Real-Time Insights

Categorical data is an oft-ignored source of valuable business intelligence. Quine makes it easy to process categorical data with your existing ETL pipeline.

Categorical data-driven apps made easy with Meroxa + thatDot

Learn how Meroxa’s Turbine makes it easy to connect data sources to Novelty Detector to create real-time anomaly detection with categorical data.

What’s the difference between Categorical and Numerical Data?

Categorical data is enormously useful but often discarded because, unlike numerical data, there were few tools available to work with it until graph DBs and streaming graph came along.

What is Categorical Data

A comprehensive and accessible consideration of categorical data, how it differs from numerical data, and why it is useful.

A Streaming Graph System For High-Volume Complex Event Processing

Stream processing and event-driven microservices are complicated! They’re complicated because they combine the hardest problems from the database domain with the hardest problems from the distributed systems domain.