Amazon DocumentDB (with MongoDB compatibility) adds Aggregation Pipeline Capabilities for Strings, Dates, and Sampling
Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads.
Amazon DocumentDB continues to increase compatibility with MongoDB and today added support for additional aggregation pipeline operators that allow you to compose powerful aggregations your documents. The new capabilities include seven aggregation string operators ($indexOfCP, $indexOfBytes, $strLenCP, $strLenBytes, $toLower, $toUpper, $split), nine date time operators ($dayOfYear, $dayOfMonth, $dayOfWeek, $year, $month, $hour, $minute, $second, and $millisecond), and the $sample aggregation pipeline stage.
To use the new features, you can create a new Amazon DocumentDB cluster with just a few clicks in the Amazon DocumentDB Management Console or you can upgrade your existing cluster.
For more information, please see the AWS Database Blog: Using new aggregation pipeline capabilities in Amazon DocumentDB to build powerful aggregation queries
Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads.
Amazon DocumentDB continues to increase compatibility with MongoDB and today added support for additional aggregation pipeline operators that allow you to compose powerful aggregations your documents. The new capabilities include seven aggregation string operators ($indexOfCP, $indexOfBytes, $strLenCP, $strLenBytes, $toLower, $toUpper, $split), nine date time operators ($dayOfYear, $dayOfMonth, $dayOfWeek, $year, $month, $hour, $minute, $second, and $millisecond), and the $sample aggregation pipeline stage.
To use the new features, you can create a new Amazon DocumentDB cluster with just a few clicks in the Amazon DocumentDB Management Console or you can upgrade your existing cluster.
For more information, please see the AWS Database Blog: Using new aggregation pipeline capabilities in Amazon DocumentDB to build powerful aggregation queries