Amazon Launches Data Processing Web Service

Amazon Web Services announced the public beta of Amazon Elastic MapReduce

April 2, 2009

2 Min Read
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SEATTLE -- Amazon Web Services LLC (AWS), a subsidiary of, Inc. (NASDAQ: AMZN), today announced the public beta of Amazon Elastic MapReduce, a web service that enables businesses, researchers, data analysts and developers to easily and cost-effectively process vast amounts of data. It utilizes a hosted Hadoop framework running on the web-scale infrastructure of Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Simple Storage Service (Amazon S3). Using Amazon Elastic MapReduce, you can instantly provision as much or as little capacity as you like to perform data-intensive tasks for distributed applications such as web indexing, data mining, log file analysis, machine learning, financial analysis, scientific simulation, and bioinformatics research. As with all AWS services, Amazon Elastic MapReduce customers will still only pay for what they use, with no up-front payments or commitments. To sign up for Amazon Elastic MapReduce and other AWS services, go to

Prior to Amazon Elastic MapReduce, running Hadoop or other MapReduce-based clusters required time-consuming set-up, management, and cluster tuning. Now, Amazon Elastic MapReduce makes it more affordable and less time consuming to run parallel compute jobs, building on top of the on-demand, resizable compute capacity of Amazon EC2. Using this service, customers can spin up and tear down Hadoop clusters on Amazon EC2 on a moments notice. To assist customers in executing these highly distributed applications, AWS is providing a number of sample applications and tutorials to get started using Amazon Elastic MapReduce.

“Some researchers and developers already run Hadoop on Amazon EC2, and many of them have asked for even simpler tools for large-scale data analysis,” said Adam Selipsky, Vice President of Product Management and Developer Relations for Amazon Web Services. “Amazon Elastic MapReduce makes crunching in the cloud much easier as it dramatically reduces the time, effort, complexity and cost of performing data-intensive tasks.”

Amazon Web Services LLC

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