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

"The ability to resize the cluster is what really makes it stand out over other Hadoop and big data solutions."

"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."

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

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

"The initial setup is straightforward."

"The project management is very streamlined."

"The solution helps us manage huge volumes of data."

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

More Amazon EMR pros

"I like the administration part."

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

"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."

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

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

Cons

"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."

"The solution can become expensive if you are not careful."

"Amazon EMR is continuously improving, but maybe something like CI/CD out-of-the-box or integration with Prometheus Grafana."

"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."

"I feel some lack of functionality in Amazon EMR."

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

"Spark jobs take longer on Amazon EMR compared to previous experiences."

More Amazon EMR cons

"The product is not user-friendly."

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

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

"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."

Pricing and Cost Advice

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

"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."

"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."

"Amazon EMR's price is reasonable."

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

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

"The cost of Amazon EMR is very high."

"The price of the solution is expensive."

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

23%

Educational Organization

13%

Computer Software Company

Healthcare Company

Financial Services Firm

17%

Comms Service Provider

Computer Software Company

Construction 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?

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...

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What needs improvement with Amazon EMR?

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What advice do you have for others considering Amazon EMR?

I am working on Amazon EMR but not extensively. Basically, our work is data transformation. Our pipelines work on that exclusively. We have Spark applications, and earlier, we used Amazon EMR exten...

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Compared 14% of the time

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Compared 9% of the time

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Compared 7% of the time

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Compared 15% of the time

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Compared 11% of the time

IBM Spectrum Computing vs HPE Data Fabric

Compared 8% of the time

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Product Reports

Buyer's Guide

Amazon EMR

January 2026

Download Amazon EMR product report

Buyer's Guide

HPE Data Fabric

December 2025

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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