Amazon EMR is a web service that makes it easy to quickly and cost-effectively process vast amounts of data.

Amazon EMR simplifies big data processing, providing a managed Hadoop framework that makes it easy, fast, and cost-effective for you to distribute and process vast amounts of your data across dynamically scalable Amazon EC2 instances. You can also run other popular distributed frameworks such as Apache Spark and Presto in Amazon EMR, and interact with data in other AWS data stores such as Amazon S3 and Amazon DynamoDB.

Amazon EMR securely and reliably handles your big data use cases, including log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Introduction to Amazon EMR (3:06)


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Amazon EMR Release Velocity

Amazon EMR Release Velocity

With versioned releases on Amazon EMR, you can easily select and use the latest open source projects on your EMR cluster, including applications in the Apache Hadoop and Spark ecosystems.  Software is installed and configured by Amazon EMR, so you spend less time on administrative tasks and can focus on increasing the value of your data.

Easy to Use

You can launch an Amazon EMR cluster in minutes. You don’t need to worry about node provisioning, cluster setup, Hadoop configuration, or cluster tuning. Amazon EMR takes care of these tasks so you can focus on analysis.

Low Cost

Amazon EMR pricing is simple and predictable: You pay an hourly rate for every instance hour you use. You can launch a 10-node Hadoop cluster for as little as $0.15 per hour. Because Amazon 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 Amazon EMR, you can provision one, hundreds, or thousands of compute instances to process data at any scale. You can easily increase or decrease the number of instances and you only pay for what you use.


You can spend less time tuning and monitoring your cluster. Amazon EMR has tuned Hadoop for the cloud; it also monitors your cluster —retrying failed tasks and automatically replacing poorly performing instances.


Amazon EMR automatically configures Amazon EC2 firewall settings that control network access to instances, and you can launch clusters in an Amazon Virtual Private Cloud (VPC), a logically isolated network you define. You can easily enable encryption for data at-rest and in-transit using Amazon EMR security configurations, including Amazon S3 server-side encryption and client-side encryption with EMRFS, on-cluster HDFS and local disk encryption, and open-source features for encryption in-transit for a variety of applications.


You have complete control over your cluster. You have root access to every instance, you can easily install additional applications, and you can customize every cluster. Amazon EMR also supports multiple Hadoop distributions and applications.

Amazon EMR can be used to analyze click stream data in order to segment users and understand user preferences. Advertisers can also analyze click streams and advertising impression logs to deliver more effective ads.

Learn how Razorfish uses EMR for click stream analysis »

Amazon EMR can be used to process vast amounts of genomic data and other large scientific data sets quickly and efficiently. Researchers can access genomic data hosted for free on AWS.

Read about the 1000 Genomes project and AWS »

Amazon EMR can be used to process logs generated by web and mobile applications. Amazon EMR helps customers turn petabytes of un-structured or semi-structured data into useful insights about their applications or users.

Learn how Yelp uses EMR to drive key website features »

Are you ready to launch your first cluster? Click here to view the Getting Started Tutorial. In the tutorial you will create a cluster that will count the frequency of words in a sample text file. In just a few minutes your cluster will be up and running.

Amazon Elastic MapReduce and Amazon EMR are trademarks of Amazon Web Services, Inc. or its affiliates. All rights reserved.