AWS Elastic MapReduce

The most reliable platform for Big Data and scalable analytics
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A NEW WAY OF PROCESSING LARGE VOLUMES OF DATA

Replacing complex on-premises clusters with a fully managed solution, AWS Elastic MapReduce (EMR) delivers scale, reliability and economics for large-scale analytics.

Recognized as one of the most widely used Big Data services in the cloud, AWS EMR allows the user to run frameworks such as Apache Spark, Apache Hadoop, Apache Hive, Presto and Apache HBase easily and efficiently. The result is a significant reduction in time, cost and complexity when processing petabytes of data. In addition, AWS EMR easily integrates with other AWS services, enabling the creation of modern, highly scalable data and analytics solutions.

How AWS EMR works

AWS EMR is a fully managed big data service that simplifies big data processing with open source tools. It automatically provisions, configures, and adjusts clusters based on demand, ensuring both flexibility and performance.

With AWS EMR, your organization can run interactive analytics, extract, transform, and load (ETL) pipelines, machine learning (ML) workloads, or large-scale log processing, without the burden of managing infrastructure.

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Benefits

  • On-demand scalability: Increase or decrease cluster capacity quickly, paying only for what you use.
  • Cost optimization: Reduce expenses with point-in-time instances and auto-scaling.
  • Native integration with the AWS ecosystem: Easily connect to Amazon S3, Amazon RDS and Amazon Redshift.
  • Reduced operational complexity: The servicehandles patching, provisioning and monitoring, freeing your team to innovate.
  • Flexible workloads: From machine learning to real-time data analytics, all in an agile and secure environment.

Practical applications

  • Big Data processing: Apache Hadoop, Apache Spark or Apache Hive workloads to analyze logs, clicks and Internet of Things data.
  • Data lakes and analytics: Creating data lakes in Amazon S3 with fast and scalable queries.
  • ML: Training and processing of large-scale distributed models.
  • Large-scale ETL: Complex data transformations with high performance and low cost.
  • Research and data science: Temporal and flexible environments for exploring massive data sets.

AWS EMR is part of an advanced analytics ecosystem within AWS:

  • Amazon S3: Secure and durable storage for large volumes of data.
  • AWS Glue: Data catalogs and pipeline orchestration.
  • Amazon CloudWatch: Cluster monitoring and observability.
  • AWS IAM: Robust security and access control.
  • Amazon SageMaker: Large-scale machine learning integrated with data processing.

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Rafael Suguihara
Head of the AWS Global Unit
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