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Amazon EMR Serverless is a new option in Amazon EMR that makes it easy and cost-effective for data engineers and analysts to run applications built using open source big data frameworks such as Apache Spark, Hive or Presto, without having to tune, operate, optimize, secure or manage clusters.
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Benefits
Speed and Value
Run big data applications and petabyte-scale data analytics faster, and at less than half the cost of on-premises solutions.
Get up to 2X faster time-to-insights with performance-optimized and open-source API-compatible versions of Spark, Hive, and Presto.
Easy builds with EMR Notebooks
Easily develop, visualize, and debug your applications using EMR Notebooks and familiar open-source tools in EMR Studio.
Use cases
Perform big data analytics
Run large-scale data processing and what-if analysis using statistical algorithms and predictive models to uncover hidden patterns, correlations, market trends, and customer preferences.
Build scalable data pipelines
Extract data from a variety of sources, process it at scale, and make it available for applications and users.
Process real-time data streams
Analyze events from streaming data sources in real-time to create long-running, highly available, and fault-tolerant streaming data pipelines.
Accelerate data science and ML adoption
Analyze data using open-source ML frameworks such as Apache Spark MLlib, TensorFlow, and Apache MXNet. Connect to Amazon SageMaker Studio for large-scale model training, analysis, and reporting.