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Distribute your data and processing across a Amazon EC2 instances using Hadoop

What is Amazon EMR?

Amazon EMR is used in a variety of applications, including log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics. Customers launch millions of Amazon EMR clusters every year.
Amazon EMR is a tool in the Big Data as a Service category of a tech stack.

Who uses Amazon EMR?

Companies
93 companies use Amazon EMR in their tech stacks, including Netflix, Yelp, and Tilt.

Developers
18 developers use Amazon EMR.

Amazon EMR Integrations

Why developers like Amazon EMR?

Here’s a list of reasons why companies and developers use Amazon EMR
Amazon EMR Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Amazon EMR in their tech stack.

Amazon EMR
AWS Glue

I use AWS Glue because I thought it was worth all they hype Fall 2018. However, you had to use Python 2.7 with no pandas support, and cold starts lasted as long as 15 minutes. Also, setting up a dev environment for iterative development was near impossible at the time.

It was a terrible experience for me. I recommend using Amazon EMR instead. Even talking with a friend that works at Amazon, they use EMR instead of Glue for internal spark workloads. Just because a company makes something doesn't mean they use that something :/

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Amazon EMR's features

  • Elastic- Amazon EMR enables you to quickly and easily provision as much capacity as you need and add or remove capacity at any time. Deploy multiple clusters or resize a running cluster
  • Low Cost- Amazon EMR is designed to reduce the cost of processing large amounts of data. Some of the features that make it low cost include low hourly pricing, Amazon EC2 Spot integration, Amazon EC2 Reserved Instance integration, elasticity, and Amazon S3 integration.
  • Flexible Data Stores- With Amazon EMR, you can leverage multiple data stores, including Amazon S3, the Hadoop Distributed File System (HDFS), and Amazon DynamoDB.
  • Hadoop Tools- EMR supports powerful and proven Hadoop tools such as Hive, Pig, and HBase.

Amazon EMR Alternatives & Comparisons

What are some alternatives to Amazon EMR?
Amazon EC2
Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale computing easier for developers.
Amazon DynamoDB
All data items are stored on Solid State Drives (SSDs), and are replicated across 3 Availability Zones for high availability and durability. With DynamoDB, you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
Hadoop
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Amazon Redshift
Redshift makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It is optimized for datasets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
Google BigQuery
Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.
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Amazon EMR's Stats

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