Amazon Redshift ML announces integration with Amazon Forecast

Amazon Redshift ML enables you to create, train, and deploy machine learning (ML) models using familiar SQL commands. With Amazon Redshift ML, you can now leverage [Amazon Forecast](https://aws.amazon.com/forecast/), a ML-based time-series forecasting service, without having to learn any new tools or having to create pipelines to move your data. With this release, you can use SQL statements to create and train forecasting models (known as predictors) from your time series data in Amazon Redshift and use these models to generate forecasts about revenue, inventory, or demand in your queries and reports. You also have the ability to generate forecasts based on the probability metrics you define. When you use forecasting in Amazon Redshift, Amazon Redshift ML uses Amazon Forecast to train the forecasting model and to generate forecasts. You pay only the associated Amazon Forecast costs. There are no additional costs associated with Amazon Redshift for creating or using Amazon Forecast models to generate predictions. View the Amazon Forecast [pricing page](https://aws.amazon.com/forecast/pricing/) for details. This feature is available in the following regions: US East (North Virgina), US-East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), and Europe (Ireland). To get started and learn more, visit the Amazon Redshift [database developers guide](https://docs.aws.amazon.com/redshift/latest/dg/r%5Fcreate%5Fmodel%5Fuse%5Fcases.html#r%5Fforecast%5Fmodel).