Amazon EMR vs HPE Data Fabric comparison

Amazon Web Services (AWS) and Hewlett Packard Enterprise are both solutions in the Hadoop category. Amazon Web Services (AWS) is ranked #3 with an average rating of 7.8, while Hewlett Packard Enterprise is ranked #4. Amazon Web Services (AWS) holds a 10.8% mindshare in H, compared to Hewlett Packard Enterprise’s 14.9% mindshare. Additionally, 83% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Hewlett Packard Enterprise users who would recommend it.

Amazon EMR

Read 25 Amazon EMR reviews

1,599 Views
560 Comparison Views

83% willing to recommend

HPE Data Fabric

Read 12 HPE Data Fabric reviews

1,152 Views
945 Comparison Views

100% willing to recommend

Amazon EMR

HPE Data Fabric

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Amazon EMR and HPE Data Fabric based on real PeerSpot user reviews.

Find out in this report how the two Hadoop solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Amazon EMR vs. HPE Data Fabric Report (Updated: December 2025).

Buyer's Guide

Amazon EMR vs. HPE Data Fabric

December 2025

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Review summaries and opinions

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

Categories and Ranking

Amazon EMR

Ranking in Hadoop

3rd

Average Rating

7.8

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (13th)

HPE Data Fabric

Ranking in Hadoop

4th

Average Rating

8.0

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2026, in the Hadoop category, the mindshare of Amazon EMR is 10.8%, down from 14.2% compared to the previous year. The mindshare of HPE Data Fabric is 14.9%, up from 14.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Hadoop Market Share Distribution
Product	Market Share (%)
Amazon EMR	10.8%
HPE Data Fabric	14.9%
Other	74.3%

Hadoop

Featured Reviews

reviewer1343079

Senior Chief Engineer (Enterprise System Presales/Postsales) at a tech vendor with 10,001+ employees

Has simplified ETL workflows with on-demand processing but needs improved cost efficiency and visibility

I have used AWS Glue with S3 for making tables and databases, but regarding Amazon EMR, I do not remember much as we are currently using it very minimally. This is my observation: In EKS, we have had to deploy by ourselves because EKS does not provide the Hadoop framework, Spark, Hive, and everything, but we have completed all the deployment ourselves. Whereas Amazon EMR provides all these things. 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. In Qubole, the interface was very good. I could see many details because in Amazon EMR console, very few details are available. In Qubole, at one link, you can get all the details of what is happening, how the processes are running, and the cost decreased by using Qubole. I found Qubole more user-friendly and cost-effective. From the security point of view, we had to open some access rights to Qubole, which might be a drawback in comparison to Amazon EMR which is native to AWS.

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Arnab Chatterjee

Regional Head of Data and Application Platform at a financial services firm with 10,001+ employees

It's flexible and easily accessible across multiple locations, but the upgrade process is complicated

Upgrading Ezmeral to a new version is a pain. They're trying to make the solution more container-friendly, so I think they're going in the right direction. The only problem we've had in the past was the upgrades. The process isn't smooth due to how the Red Hat operating system upgrades currently work. They're transforming their host stack to increase cloud readiness and edge compute capability. HPE is transitioning from a standard data-driven approach to one powered by AI analytics. That's something they have released very recently. I haven't tried that, but it will probably make things easier. The ability to adapt Ezmeral to the public cloud is probably missing. I've heard that they're getting leaner. However, it doesn't have a clear managed services offering for you if you want to deploy this stack on the cloud. That's a problem. This probably won't meet your needs if you require consistency across on-prem and the cloud. It's not Ezmeral's fault. None of the products would fit the bill. Cloud offerings are biased towards their own implementation. It's a general issue on most big data platforms. They're already working towards that, but it hasn't been released.

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Quotes from Members

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

Pros

"Amazon EMR has multiple connectors that can connect to various data sources."

"The initial setup is straightforward."

"It allows users to access the data through a web interface."

"It has a variety of options and support systems."

"Amazon EMR provides out-of-the-box functionality because we can deploy and get Spark functionality over Hadoop."

"In Amazon EMR it is easy to rebuild anything, easy to upgrade and has good fault tolerance."

"The security of the managed workflow and the managed services are the best features for us. Since we inherited their security model and it's all managed services, those are the key benefits for our clients."

"Amazon EMR is a good solution that can be used to manage big data."

More Amazon EMR pros

"HPE Ezmeral Data Fabric can be accessed from any namespace globally as you would access it from a machine using an NFS."

"I like the administration part."

"My customers find the product cheaper compared to other solutions. The previous solution that we used did not have unified analytics like the runtime or the analog."

"The model creation was very interesting, especially with the libraries provided by the platform."

"It is a stable solution...It is a scalable solution."

Cons

"There is room for improvement in pricing."

"The legacy versions of the solution are not supported in the new versions."

"The product's features for storing data in static clusters could be better."

"The initial setup was time-consuming."

"The product must add some of the latest technologies to provide more flexibility to the users."

"There is no need to pay extra for third-party software."

"As people are shifting from legacy solutions to other technologies, Amazon EMR needs to add more features that give more flexibility in managing user data."

"The dashboard management could be better. Right now, it's lacking a bit."

More Amazon EMR cons

"The deployment could be faster. I want more support for the data lake in the next release."

"HPE Ezmeral Data Fabric is not compatible with third-party tools."

"Upgrading Ezmeral to a new version is a pain. They're trying to make the solution more container-friendly, so I think they're going in the right direction. The only problem we've had in the past was the upgrades. The process isn't smooth due to how the Red Hat operating system upgrades currently work."

"The product is not user-friendly."

"Having the ability to extend the services provided by the platform to an API architecture, a micro-services architecture, could be very helpful."

Pricing and Cost Advice

"You don't need to pay for licensing on a yearly or monthly basis, you only pay for what you use, in terms of underlying instances."

"The product is not cheap, but it is not expensive."

"There is no need to pay extra for third-party software."

"The cost of Amazon EMR is very high."

"Amazon EMR is not very expensive."

"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 price of the solution is expensive."

"There is a small fee for the EMR system, but major cost components are the underlying infrastructure resources which we actually use."

More Amazon EMR pricing and cost advice

"HPE is flexible with you if you are an existing customer. They offer different models that might be beneficial for your organization. It all depends on how you negotiate."

"There is a need for my company to pay for the licensing costs of the solution."

"The tool's price is cheap and based on a usage basis. The solution's licensing costs are yearly and there are no extra costs."

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Top Industries

By visitors reading reviews

Financial Services Firm

22%

Educational Organization

13%

Computer Software Company

Healthcare Company

Financial Services Firm

18%

Comms Service Provider

Performing Arts

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	5
Large Enterprise	12

By reviewers
Company Size	Count
Small Business	4
Large Enterprise	7

Questions from the Community

What is your experience regarding pricing and costs for Amazon EMR?

I would rate the price for Amazon EMR, where one is high and ten is low, as a good one.

See all answers

What needs improvement with Amazon EMR?

I feel some lack of functionality in Amazon EMR. I have thoughts on what would be great to see in the product, such as AI/ML features or additional options.

See all answers

What advice do you have for others considering Amazon EMR?

I find it easy to integrate Amazon EMR with other AWS services like S3 or EC2 for data processing needs. I would rate this review as eight out of ten.

See all answers

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Comparisons

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Compared 23% of the time

Cloudera Distribution for Hadoop vs Amazon EMR

Compared 12% of the time

Apache Spark vs Amazon EMR

Compared 8% of the time

Amazon Redshift vs Amazon EMR

Compared 8% of the time

Azure Data Factory vs Amazon EMR

Compared 5% of the time

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Cloudera Distribution for Hadoop vs HPE Data Fabric

Compared 24% of the time

Cloudera Data Platform vs HPE Data Fabric

Compared 15% of the time

Apache Spark vs HPE Data Fabric

Compared 10% of the time

IBM Spectrum Computing vs HPE Data Fabric

Compared 8% of the time

IBM Analytics Engine vs HPE Data Fabric

Compared 8% of the time

More HPE Data Fabric Competitors

Product Reports

Buyer's Guide

Amazon EMR

January 2026

Download Amazon EMR product report

Buyer's Guide

HPE Data Fabric

January 2026

Download HPE Data Fabric product report

Also Known As

Amazon Elastic MapReduce

MapR, MapR Data Platform

Overview

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.

Amazon Web Services (AWS)

Forward-leaning companies win market share because they leverage data more effectively than their competitors. Unlock the potential of your data assets with HPE Ezmeral Data Fabric (formerly MapR Data Platform). Empower your data science, analytics, and business teams by simplifying data management on a globally distributed scale. All with enterprise-grade reliability, security, and performance.

Hewlett Packard Enterprise

Sample Customers

Yelp

Valence Health, Goodgame Studios, Pico, Terbium Labs, sovrn, Harte Hanks, Quantium, Razorsight, Novartis, Experian, Dentsu ix, Pontis Transitions, DataSong, Return Path, RAPP, HP

Buyer's Guide

Amazon EMR vs. HPE Data Fabric

December 2025

Free Report: Amazon EMR vs. HPE Data Fabric

Find out what your peers are saying about Amazon EMR vs. HPE Data Fabric and other solutions. Updated: December 2025.

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