EMR launches clusters in minutes. You don’t need to worry about node provisioning, infrastructure setup, Hadoop configuration, or cluster tuning. EMR takes care of these tasks so you can focus on analysis. Analysts, data engineers, and data scientists can launch a serverless Jupyter notebook in seconds using EMR Notebooks, allowing individuals and teams to collaborate and interactively explore, process and visualize data in an easy to use notebook format.

EMR pricing is simple and predictable: You pay a per-instance rate for every second used, with a one-minute minimum charge. You can launch a 10-node EMR cluster with applications such as Apache Spark, and Apache Hive, for as little as $0.15 per hour. Because EMR has native support for Amazon EC2 Spot and Reserved Instances, you can also save 50-80% on the cost of the underlying instances.

With EMR, you can provision one, hundreds, or thousands of compute instances to process data at any scale. The number of instances can be increased or decreased manually or automatically using Auto Scaling (which manages cluster sizes based on utilization), and you only pay for what you use. Unlike the rigid infrastructure of on-premise clusters, EMR decouples compute and persistent storage, giving you the ability to scale each independently.

Spend less time tuning and monitoring your cluster. EMR is tuned for the cloud, and constantly monitors your cluster — retrying failed tasks and automatically replacing poorly performing instances. EMR provides the latest stable open source software releases, so you don’t have to manage updates and bug fixes, leading to fewer issues and less effort to maintain the environment. With multiple master nodes, clusters are highly available and automatically failover in the event of a node failure.

EMR automatically configures EC2 firewall settings controlling network access to instances, and launches clusters in an Amazon Virtual Private Cloud (VPC), a logically isolated network you define. For objects stored in S3, server-side encryption or client-side encryption can be used with EMRFS (an object store for Hadoop on S3), using the AWS Key Management Service or your own customer-managed keys. EMR makes it easy to enable other encryption options, like in-transit and at-rest encryption, and strong authentication with Kerberos.

You have complete control over your cluster. You have root access to every instance, you can easily install additional applications, and customize every cluster with bootstrap actions. You can also launch EMR clusters with custom Amazon Linux AMIs, and reconfigure running clusters on the fly without the need to re-launch the cluster.