Use ML predictions over Amazon DynamoDB data with Amazon Athena ML
Today’s modern applications use multiple purpose-built database engines, including relational, key-value, document, and in-memory databases. This purpose-built approach improves the way applications use data by providing better performance and reducing cost. However, the approach raises some challenges for data teams that need to provide a holistic view on top of these database engines, and especially when they need to merge the data with datasets in the organization’s data lake.