Author: Ben Lackey

Graph databases are useful for solving problems related to connected data, and represent data as nodes and enable organizations to uncover relationships between data that’s not possible with other approaches. Experts from AWS and Neo4j explore four types of databases and the most common applications for each: relational, document, in-memory, and graph. We’ll cover how different industries use graph databases and how they work as part of an AWS architecture.

Featurization is one of the most difficult problems in machine learning. Learn how graph features engineered in Neo4j can be used in a supervised learning model trained with Amazon SageMaker. These novel graph features can improve model performance beyond what’s possible with more traditional approaches. Together, these components offer a graph platform that can be used to understand graph data and operationalize graph use cases.