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Amazon EMR Reviews

Vendor: Amazon Web Services (AWS)
3.9 out of 5
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What is Amazon EMR?

Amazon EMR simplifies big data processing by offering integration with popular tools. It's scalable and cost-efficient, enabling fast processing while managing infrastructure effortlessly. It's designed for users aiming to streamline data workflows and leverage its batch processing capabilities effectively.

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Amazon EMR is the #3 ranked solution in top Hadoop solutions and #13 ranked solution in top Cloud Data Warehouse solutions. PeerSpot users give Amazon EMR an average rating of 7.8 out of 10. Amazon EMR is most commonly compared to Databricks: Amazon EMR vs Databricks. Amazon EMR is popular among the large enterprise segment, accounting for 55% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 21% of all views.
Buyer's Guide
Amazon EMR
May 2026
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Amazon EMR mindshare

Product category:
Hadoop
As of May 2026, the mindshare of Amazon EMR in the Hadoop category stands at 10.2%, down from 13.9% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Hadoop Mindshare Distribution
ProductMindshare (%)
Amazon EMR10.2%
Cloudera Distribution for Hadoop14.8%
Apache Spark13.6%
Other61.4%
Hadoop

PeerResearch reports based on Amazon EMR reviews

TypeTitleDate
CategoryHadoopMay 8, 2026Download
ProductReviews, tips, and advice from real usersMay 8, 2026Download
ComparisonAmazon EMR vs Apache SparkMay 8, 2026Download
ComparisonAmazon EMR vs Cloudera Distribution for HadoopMay 8, 2026Download
ComparisonAmazon EMR vs HPE Data FabricMay 8, 2026Download
Suggested products
TitleRatingMindshareRecommending
Databricks4.1N/A96%93 interviewsAdd to research
Teradata4.1N/A88%83 interviewsAdd to research
 
 
Key learnings from peers

Valuable Features

Amazon EMR offers scalability, auto-scaling capabilities, and cost-effectiveness. It integrates easily with Hadoop and HDFS, using Amazon EC2 and Amazon S3 for dynamic storage. The platform simplifies management tasks, supports data transformation with ETL processes, and provides robust security. Users appreciate the flexible cluster resizing, stability, affordability, and versatility in managing big data. With managed services and out-of-the-box functionality, EMR is accessible for diverse data tasks.
  • "We are using applications, such as Splunk, Livy, Hadoop, and Spark; we are using all of these applications in Amazon EMR and they're helping us a lot."
  • "It's made life very easy."
  • "One of the valuable features about this solution is that it's managed services, so it's pretty stable, and scalable as much as you wish."

Room for Improvement

Amazon EMR could improve its user interface and simplify the initial learning curve. Cost management and pricing control can be challenging with scaling. Cluster configuration is complicated, and startup times are slow. Web support and feature integration need enhancements. Some versions showed compatibility issues. Customers would benefit from improved monitoring, debugging, and stability. Automation for deployment, cluster sizing, and better integration with other AWS services could be advantageous.
  • "The cost of Amazon EMR is very high."
  • "We don't have much control. If we have multiple users, if they want to scale up, the cost will go and increase and we don't know how we can restrict that price part."
  • "Amazon EMR is continuously improving, but maybe something like CI/CD out-of-the-box or integration with Prometheus Grafana."

ROI

Various viewpoints indicate that Amazon EMR's return on investment fluctuates depending on vendors and usage. Responses emphasize high returns, especially for those transitioning from on-premise systems, with expectations of at least two-to-one returns. Some report noticeable savings of up to 20%. While specific figures are often not calculated, and some can't provide precise return details, feedback suggests that it generally results in substantial cost efficiencies and savings for companies.

Pricing

Enterprise buyers evaluating Amazon EMR find its pricing reliant on usage and integration, with costs mainly driven by infrastructure resources, particularly EC2 fees. Users appreciate the lack of additional licensing costs, but some note the service can be expensive compared to competitors. Cost control is possible with strategic resource management and careful monitoring, as unexpected charges can arise. Monthly expenditures can vary, with large enterprises spending significantly more annually based on their needs.
  • "I rate the tool's pricing a five out of ten. It can be expensive since it's a managed service, and if you are not careful, you can run into unexpected charges. You can make a mistake that costs you tens of thousands of dollars. That's happened to us twice, so I'm sensitive to it. We're still trying to work on that. Our smallest client probably spends a hundred thousand dollars yearly on licensing, while our largest is well over a million."
  • "The product is not cheap, but it is not expensive."
  • "Amazon EMR is not very expensive."

Popular Use Cases

Amazon EMR is utilized for running Spark scripts, building data lakes, and handling tech processing. It supports complex algorithms, data pipelines, large databases, and big data frameworks. Organizations migrate processes to the cloud, leveraging EMR for cloud-based management, serverless architecture, and data analysis. EMR is also used in industry-specific applications, data transformation, and integration with AWS services like SageMaker, Airflow, and S3.

Service and Support

Amazon EMR's customer service has mixed ratings, with some finding it great, while others find it inconsistent. Technical support generally receives positive feedback for being knowledgeable and responsive, though some users report slower response times when integrating with open-source solutions. Many users appreciate having access to responsive support, particularly when encountering urgent issues, and benefit from 24/7 availability and comprehensive assistance with technical inquiries, billing, and deployment activities.

Deployment

Amazon EMR's initial setup is mostly perceived as straightforward, especially for users familiar with the tool and big data concepts. Some users find it complex due to configuration challenges and issues with multi-factor authentication. Deployment can be done quickly via AWS Console or Terraform. Initial setup duration varies, ranging from 30 minutes to several weeks, influenced by documentation use, team expertise, and specific project requirements.

Scalability

Amazon EMR is considered scalable by several organizations, with capabilities to tailor clusters using memory, storage, or GPU needs. Companies expand usage gradually, leveraging auto-scaling, EC2, and on-demand instances. Managed services ensure extensive scaling, although occasionally, resource allocation may lag. It supports enterprises and vast user bases, processing substantial data volumes. Despite minor performance issues, it suits data analytics and customization for specific cases, enabling seamless scaling for diverse organizational requirements.

Stability

Users find Amazon EMR stable, with high availability and reliability. Some recommend monitoring configurations as data changes, but issues are minimal. Users rate its steadiness highly, noting its support from availability zones, failover capabilities, and fault tolerance. Regular updates, monitoring, logging, and disaster recovery contribute positively. Despite occasional minor issues, users express confidence in its performance, suggesting it meets expectations in most scenarios. Stability ratings are generally eight to nine out of ten.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
Download our Amazon EMR Buyer's Guide for additional reliable information.

Review data by company size

By reviewers
Company SizeCount
Small Business6
Midsize Enterprise4
Large Enterprise10
By reviewers
By visitors reading reviews
Company SizeCount
Small Business63
Midsize Enterprise29
Large Enterprise111
By visitors reading reviews

Top industries

By visitors reading reviews
Financial Services Firm
21%
Healthcare Company
9%
Manufacturing Company
8%
Performing Arts
5%
Construction Company
5%
Comms Service Provider
5%
Computer Software Company
5%
Hospitality Company
4%
University
3%
Retailer
3%
Educational Organization
3%
Media Company
3%
Government
3%
Marketing Services Firm
2%
Energy/Utilities Company
2%
Insurance Company
2%
Real Estate/Law Firm
2%
Wholesaler/Distributor
1%
Consumer Goods Company
1%
Logistics Company
1%
Outsourcing Company
1%
Transportation Company
1%

Compare Amazon EMR with alternative products

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Learn more about Amazon EMR

Amazon EMR is a managed service that provides robust features for big data processing. It integrates seamlessly with S3, EC2, Hive, and Spark to facilitate sophisticated data transformation tasks and infrastructure management. It allows organizations to run data lakes, Spark, and Hadoop clusters effortlessly, offering flexibility with on-demand execution and extensive scalability. The platform is valued for its strong processing speed and comprehensive security features, making it ideal for complex data engineering projects. It supports both batch processing and real-time workflows, designed to eliminate hardware management while maintaining cost efficiency and stability.

What are the key features of Amazon EMR?
  • Cluster Management: Offers intuitive control and configuration of clusters
  • Integration: Seamlessly integrates with S3, EC2, Spark, and more
  • Scalability: Provides flexible scaling to meet data demands
  • Batch Processing: Allows efficient handling of large data sets
  • Cost Efficiency: Minimizes costs with managed service offerings
What benefits and ROI should be considered?
  • Processing Speed: Fast performance for data processing tasks
  • Security: Built-in features ensure data protection
  • Infrastructure Simplification: Eliminates hardware management needs
  • Flexibility: Adapts to changing data loads with ease
  • Affordability: Offers economic processing power

Amazon EMR is implemented by industries such as healthcare and tech processing for complex data tasks like building data lakes or financial data processing. It supports AI-driven analytics and data engineering projects, integrating with SageMaker for predictions and maintaining workflows in public health applications, allowing professionals in different fields to manage data pipelines, resource utilization, and job execution efficiently.

Amazon EMR was previously known as Amazon Elastic MapReduce.

Amazon EMR customers

Yelp

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Product Categories

Product Categories
Hadoop
Cloud Data Warehouse

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Amazon EMR Reviews Summary
Author infoRatingReview Summary
Senior Chief Engineer (Enterprise System Presales/Postsales) at a tech vendor with 10,001+ employees3.0I've used Amazon EMR mainly for Spark-based ETL, but we've shifted 95% to EKS due to better cost control. EMR is simple and integrates well but lacks detailed UI and is costlier compared to pod-level control on EKS.
Senior Technical Engineer at a transportation company with 5,001-10,000 employees4.0I use Amazon EMR for data processing and ETL, finding its customizable features valuable, though it could improve with AI/ML capabilities. It's stable, integrates well with AWS services, and support is excellent, but setup could be simpler.
Lead AWS Data Engineer at Fission Labs5.0I have used Amazon EMR for data engineering projects, focusing on job submission and resource management. Its cluster properties and integration with big data tools are valuable, though improvements are needed in retries, data handling, scalability, and integration.
Director of Data Science at HealthWorks Analytics3.5I find Amazon EMR valuable for maintaining client workflows in the healthcare sector due to its security features as a managed service. It offers a high ROI but can be expensive if not carefully managed on AWS.
Vice President -Product Management at Paytm4.5I use Amazon EMR to help American Express process and analyze data. Its multiple connectors and cost-effective processing are valuable, though Spark jobs are slower. The service integrates well with other storage solutions, potentially saving 20% in costs.
Data Governance Manager at VPBFC4.5We use Amazon EMR for data processing, reading data from S3 and writing it back there post-processing. Its affordable pricing and seamless integration with open-source platforms are valuable, though its stability could improve. We haven't considered alternate solutions.
AWS / Big Data Engineer at Waste Management, Inc.4.0I found Amazon EMR Serverless ideal for deploying online applications, as it simplifies resource management. While pricing could be improved, the solution offers better ROI and substantial savings. We migrated from a server-based setup to AWS for this service.
Senior Software Development Engineer at Yahoo!3.0I use EMR with Spark for large cloud jobs. While stable and scalable, its very slow start-up time is a significant problem for frequent, short tasks, impacting costs. Support is also slower than desired. I'd rate it a 6/10.