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Amazon EMR vs Cloudera Distribution for Hadoop comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
5.4
Amazon EMR delivers significant cost savings and efficiency, with some users achieving up to 20% savings and positive ROI.
Sentiment score
5.5
Measuring ROI from Cloudera Distribution for Hadoop is complex due to diverse applications, pricing, and evaluation difficulties.
 

Customer Service

Sentiment score
7.7
Amazon EMR support is generally proactive and responsive, though user experiences vary, especially during open-source integrations.
Sentiment score
6.5
Cloudera's Hadoop support receives mixed reviews, with users praising responsiveness while noting concerns on quality and accessibility.
We get all call support, screen sharing support, and immediate support, so there are no problems.
They help with billing, cost determination, IAM properties, security compliance, and deployment and migration activities.
The technical support is quite good and better than IBM.
 

Scalability Issues

Sentiment score
7.4
Amazon EMR is scalable and versatile, though some face resource speed issues and performance differences between environments.
Sentiment score
7.7
Cloudera Distribution for Hadoop is highly scalable and flexible, suitable for large deployments but can be costly to expand.
Scalability can be provisioned using the auto-scaling feature, EC2 instances, on-demand instances, and storage locations like block storage, S3, or file storage.
 

Stability Issues

Sentiment score
7.7
Amazon EMR is stable and reliable, with high availability, but could improve slightly to address occasional concerns.
Sentiment score
7.3
Cloudera Distribution for Hadoop has mixed stability reviews, with hardware issues noted, but support and workarounds are available.
Regular updates, patch installations, monitoring, logging, alerting, and disaster recovery activities are crucial for maintaining stability.
We faced challenges but overcame those challenges successfully.
 

Room For Improvement

Amazon EMR requires improved user-friendliness, stability, monitoring, integration, and pricing adjustments to enhance performance, scalability, and compatibility.
Cloudera Distribution for Hadoop struggles with stability and integration, needing better performance, security, documentation, and modern deployment solutions.
The cost factor differs significantly. When you run Spark application on EKS, you run at the pod level, so you can control the compute cost. But in Amazon EMR, when you have to run one application, you have to launch the entire EC2.
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.
Integrating with Active Directory, managing security, and configuration are the main concerns.
 

Setup Cost

Amazon EMR pricing is usage-based, perceived higher, but optimizable through instance management and auto-scaling for Big Data tasks.
Cloudera's Hadoop distribution is costly, aimed at large enterprises, lacking a community version, with per-node licensing.
Costs are involved based on cluster resources, data volumes, EC2 instances, instance sizes, Kubernetes, Docker services, storage, and data transfers.
It can be deployed on-premises, unlike competitors' cloud-only solutions.
 

Valuable Features

Amazon EMR offers scalable, cost-effective data processing with easy integration, advanced features, and robust management on a cloud-based infrastructure.
Cloudera for Hadoop offers easy installation, robust security, tool integration, scalability, and supports on-premises and cloud environments.
Amazon EMR helps in scalability, real-time and batch processing of data, handling efficient data sources, and managing data lakes, data stores, and data marts on file systems and in S3 buckets.
Amazon EMR provides out-of-the-box functionality because we can deploy and get Spark functionality over Hadoop.
This is the only solution that is possible to install on-premise.
 

Categories and Ranking

Amazon EMR
Ranking in Hadoop
3rd
Average Rating
7.8
Reviews Sentiment
7.0
Number of Reviews
24
Ranking in other categories
Cloud Data Warehouse (13th)
Cloudera Distribution for H...
Ranking in Hadoop
1st
Average Rating
8.0
Reviews Sentiment
6.3
Number of Reviews
51
Ranking in other categories
NoSQL Databases (8th)
 

Mindshare comparison

As of October 2025, in the Hadoop category, the mindshare of Amazon EMR is 12.8%, down from 14.3% compared to the previous year. The mindshare of Cloudera Distribution for Hadoop is 21.9%, down from 26.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Hadoop Market Share Distribution
ProductMarket Share (%)
Cloudera Distribution for Hadoop21.9%
Amazon EMR12.8%
Other65.3%
Hadoop
 

Featured Reviews

Prashant  Singh - PeerSpot reviewer
Seamless data integration enhances reporting efficiency and an easy setup
Amazon EMR has multiple connectors that can connect to various data sources. The service charges are based on processing only, depending on the resources used, which can help save money. It is easy to integrate with other services for storage, allowing data to be shifted to cheaper storage based on usage.
Rok Dolinsek - PeerSpot reviewer
Enables on-premise implementation with powerful data processing capabilities
This is the only solution that is possible to install on-premise. Cloudera provides a hybrid solution that combines compute on cloud or on-premises. It includes all machine learning algorithms in the Spark machine learning library. All functionalities needed for a big data platform and ETL are on the platform, eliminating the need for other tools. It is scalable, ready for vertical scaling, and very powerful, offering numerous functionalities and configurations for generative AI.
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Top Industries

By visitors reading reviews
Financial Services Firm
23%
Computer Software Company
12%
Educational Organization
12%
Healthcare Company
7%
Educational Organization
18%
Financial Services Firm
18%
Computer Software Company
11%
Energy/Utilities Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise5
Large Enterprise11
By reviewers
Company SizeCount
Small Business16
Midsize Enterprise9
Large Enterprise31
 

Questions from the Community

What do you like most about Amazon EMR?
Amazon EMR is a good solution that can be used to manage big data.
What is your experience regarding pricing and costs for Amazon EMR?
Compared to others, Amazon seems efficient and is considered good for Big Data workloads. Costs are involved based on cluster resources, data volumes, EC2 ( /products/amazon-ec2-reviews ) instances...
What needs improvement with Amazon EMR?
There is room for improvement with respect to retries, handling the volume of data on S3 ( /products/amazon-s3-reviews ) buckets, cluster provisioning, scaling, termination, security, and integrati...
What do you like most about Cloudera Distribution for Hadoop?
The tool can be deployed using different container technologies, which makes it very scalable.
What is your experience regarding pricing and costs for Cloudera Distribution for Hadoop?
The price for Cloudera is average, yet it is very good compared to other solutions. It can be deployed on-premises, unlike competitors' cloud-only solutions.
What needs improvement with Cloudera Distribution for Hadoop?
If they could support modifying the data more easily than the current implementation, it would be beneficial.
 

Also Known As

Amazon Elastic MapReduce
No data available
 

Overview

 

Sample Customers

Yelp
37signals, Adconion,adgooroo, Aggregate Knowledge, AMD, Apollo Group, Blackberry, Box, BT, CSC
Find out what your peers are saying about Amazon EMR vs. Cloudera Distribution for Hadoop and other solutions. Updated: September 2025.
869,883 professionals have used our research since 2012.