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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 Elastic MapReduce (Amazon EMR) is a web service that makes it easy to quickly and cost-effectively process vast amounts of data. Amazon EMR simplifies big data processing, providing a managed Hadoop framework that makes it easy, fast, and cost-effective for you to distribute and process vast amounts of your data across dynamically scalable Amazon EC2 instances.
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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 Azure Data Factory: Amazon EMR vs Azure Data Factory. Amazon EMR is popular among the large enterprise segment, accounting for 69% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 23% of all views.
Buyer's Guide
Amazon EMR
October 2025
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Amazon EMR mindshare

Product category:
Hadoop
As of October 2025, the mindshare of Amazon EMR in the Hadoop category stands at 12.8%, down from 14.3% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Hadoop Market Share Distribution
ProductMarket Share (%)
Amazon EMR12.8%
Cloudera Distribution for Hadoop21.9%
Apache Spark19.0%
Other46.3%
Hadoop

PeerResearch reports based on Amazon EMR reviews

TypeTitleDate
CategoryHadoopOct 13, 2025Download
ProductReviews, tips, and advice from real usersOct 13, 2025Download
ComparisonAmazon EMR vs Cloudera Distribution for HadoopOct 13, 2025Download
ComparisonAmazon EMR vs Apache SparkOct 13, 2025Download
ComparisonAmazon EMR vs HPE Ezmeral Data FabricOct 13, 2025Download
Suggested products
TitleRatingMindshareRecommending
Azure Data Factory4.0N/A92%92 interviewsAdd to research
Teradata4.1N/A87%77 interviewsAdd to research
 
 
Key learnings from peers

Valuable Features

Amazon EMR offers scalability and efficiency, auto-scaling capabilities, stability, ease of integration with Hadoop, and access to AWS services like S3 and EC2. It eliminates hardware management, is cost-effective, and provides a managed service experience. Users appreciate its data processing speed, storage capacity, security features, and flexibility to integrate with multiple data sources and tools, enhancing Big Data and AI tasks, while supporting structured and unstructured data handling.
  • "Amazon EMR provides out-of-the-box functionality because we can deploy and get Spark functionality over Hadoop."
  • "I rate Amazon EMR as ten out of ten."
  • "Amazon EMR has multiple connectors that can connect to various data sources."

Room for Improvement

Amazon EMR faces challenges with setting up certain tasks and a steep learning curve for newcomers. The web interface lacks user-friendliness, requiring more intuitive customization options. Stability and cost issues need addressing, particularly with version updates disrupting workflows. Improved monitoring, debugging, cluster configuration, startup times, and integration with other services are desired enhancements. Users seek better scalability, MLOps support, and interface advancements similar to Apache, as well as better cost management and flexibility in technology adaptation.
  • "In Qubole, the interface was very good. I could see many details because in Amazon EMR console, very few details are available."
  • "There is room for improvement with respect to retries, handling the volume of data on S3 buckets, cluster provisioning, scaling, termination, security, and integration between services like S3, Glue, Lake Formation, and DynamoDB."
  • "Spark jobs take longer on Amazon EMR compared to previous experiences."

ROI

Amazon EMR's return varies widely depending on vendor and usage details. Many entities describe it as offering significant savings, with costs reduced by up to 20%. Customer responses indicate a high return for those transitioning from on-premise systems, often achieving returns of two to one or greater on their investments. Although not universally measured or calculated, Amazon EMR generally provides favorable monetary returns when aligned with specific business needs.

Pricing

Enterprise users experience varied pricing with Amazon EMR, influenced by usage and integration. Some find it expensive, especially for large-scale operations with monthly costs ranging from $40,000 to $50,000. Overheads include underlying infrastructure like EC2 fees and cluster usage. No annual licensing fees, only pay-per-use. While some deem it moderately priced, others caution about unexpected charges. Cost efficiency can be achieved through cluster sharing and auto-scaling. Gold support packages contribute to higher costs.
  • "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

Organizations primarily utilize Amazon EMR for processing big data, running Spark scripts, and managing data pipelines. It handles large-scale tech and data engineering projects, supports AI-driven tasks, and facilitates data analytics by integrating with AWS services like S3 and SageMaker. EMR is used for processing data from diverse sources, constructing data lakes, and ensuring efficient data operations. Many are transitioning to cloud-based, serverless architectures for streamlined data handling and execution.

Service and Support

Amazon EMR customer service and support quality varies, with some experiences noting inconsistency. Several users describe the technical support as knowledgeable and responsive, while others highlight delays in integration-related responses. Many express satisfaction, benefiting from quick and effective assistance. Premier partners report having comprehensive support, while some mention satisfactory response times and round-the-clock availability. Although some face challenges, many find technical support proficient and helpful, frequently mentioning fast problem resolution.

Deployment

Many find Amazon EMR's initial setup straightforward. Some mention it becomes easier with experience and documentation can be helpful. A few report complexity, especially with configuration and MFA reset. Commonly, small teams manage deployment and maintenance. The time needed varies, typically from 30 minutes to a few weeks, influenced by project needs and expertise. Many appreciate the option to automate setup via scripts and AWS Console, enhancing speed and simplicity.

Scalability

Amazon EMR scales efficiently for various organizations with different user counts, leveraging its managed services. It offers customizable scaling via clusters, instances, and storage options. Some note significant user counts, engineering-specific utilization, and significant data processing capabilities. Challenges exist in resource allocation time and computing power for some. Monitoring and alerts are crucial for effective scaling. Organizations utilize it across diverse scales and anticipate future expansion.

Stability

Users indicate Amazon EMR is generally stable. Reports suggest occasional configuration requirements depending on data size, yet it consistently performs well without bugs or crashes. Many appreciate its high availability, reliability, and fault tolerance, supported by features like availability zones, failover capabilities, and regular maintenance activities. Although some believe its stability could be slightly enhanced, ratings mostly range from 8.5 to 9 out of 10, highlighting its robustness and effectiveness in handling tasks.
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 Enterprise9
By reviewers
By visitors reading reviews
Company SizeCount
Small Business57
Midsize Enterprise34
Large Enterprise198
By visitors reading reviews

Top industries

By visitors reading reviews
Financial Services Firm
23%
Computer Software Company
12%
Educational Organization
12%
Healthcare Company
7%
Manufacturing Company
6%
Media Company
4%
Performing Arts
4%
Retailer
4%
University
4%
Comms Service Provider
3%
Construction Company
3%
Government
3%
Hospitality Company
2%
Energy/Utilities Company
2%
Real Estate/Law Firm
2%
Insurance Company
1%
Consumer Goods Company
1%
Transportation Company
1%
Logistics Company
1%
Legal Firm
1%
Recreational Facilities/Services Company
1%

Compare Amazon EMR with alternative products

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Learn more about Amazon EMR

Amazon EMR was previously known as Amazon Elastic MapReduce.

Amazon EMR customers

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Product Categories

Product Categories
Hadoop
Cloud Data Warehouse

Popular Comparisons

Popular Comparisons
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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.
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.
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.
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.
Hadoop Administrator at Capgemini4.0No summary available
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.
Vice President -Product Management at Paytm3.5No summary available