DGL Empowers Service for Predictions on Connected Datasets with Graph Neural Networks

AWS just announced the availability of Neptune ML. Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. Neptune ML is a new capability that uses graph neural networks (GNNs), a machine learning (ML) technique purpose-built for graphs, for making easy, fast, and accurate predictions on graphs. The accuracy of most predictions for graphs increases to 50% with Neptune ML when compared to non-graph methods. Neptune ML uses the Deep Graph Library (DGL), an open-source library to which AWS contributes that makes it easy to develop and apply GNN models on graph data. Now, developers can create, train, and apply ML on Neptune data in hours instead of weeks without the need to learn new tools and ML technologies.

We would love to see more commercial vendors build innovation on top of DGL in the future. For more information about Neptune ML, please visit the AWS blog and product page. Watch the re:Invent 2020 Machine Learning Keynote by Swami Sivasubramanian for the full announcement.