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 8.5, while Hewlett Packard Enterprise is ranked #4 with an average rating of 8.0. Amazon Web Services (AWS) holds a 12.8% mindshare in H, compared to Hewlett Packard Enterprise’s 14.4% mindshare. Additionally, 82% 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 24 Amazon EMR reviews

1,621 Views
567 Comparison Views

82% willing to recommend

HPE Data Fabric

Read 12 HPE Data Fabric reviews

1,085 Views
901 Comparison Views

100% willing to recommend

Amazon EMR

HPE Data Fabric

Comparison Buyer's Guide

Download the report

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: September 2025).

Buyer's Guide

Amazon EMR vs. HPE Data Fabric

September 2025

Download the complete report

Helped 872,655 peers since 2012

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 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 HPE Data Fabric is 14.4%, up from 13.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Hadoop Market Share Distribution
Product	Market Share (%)
Amazon EMR	12.8%
HPE Ezmeral Data Fabric	14.4%
Other	72.8%

Hadoop

Featured Reviews

Prashant Singh

Vice President -Product Management at Paytm

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.

Read full review

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.

Read full review

Quotes from Members

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

Pros

"This is the best tool for hosts and it's really flexible and scalable."

"Amazon EMR's most valuable features are processing speed and data storage capacity."

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

"The solution is pretty simple to set up."

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

"The initial setup is pretty straightforward."

"When we grade big jobs from on-prem to the cloud, we do it in EMR with Spark."

"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."

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."

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

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

"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."

Cons

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

"The most complicated thing is configuring to the cluster and ensure it's running correctly."

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

"There is room for improvement in pricing."

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

"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."

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

"There were times where they would release new versions and it seemed to end up breaking old versions, which is very strange."

More Amazon EMR cons

"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."

"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."

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

"The product is not user-friendly."

Pricing and Cost Advice

"Amazon EMR's price is reasonable."

"The product is not cheap, but it is not 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 cost of Amazon EMR is very high."

"The price of the solution is 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."

"Amazon EMR is not very 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."

"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."

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

See which vendors are best for you

Use our free recommendation engine to learn which Hadoop solutions are best for your needs.

See recommendations

872,655 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

23%

Computer Software Company

13%

Educational Organization

12%

Healthcare Company

Financial Services Firm

15%

Computer Software Company

13%

Comms Service Provider

12%

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	5
Large Enterprise	11

By reviewers
Company Size	Count
Small Business	4
Large Enterprise	7

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.

See all answers

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...

See all answers

What needs improvement with Amazon EMR?

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 h...

See all answers

Ask a question

Earn 20 points

Comparisons

Snowflake vs Amazon EMR

Compared 30% of the time

Cloudera Distribution for Hadoop vs Amazon EMR

Compared 20% of the time

Apache Spark vs Amazon EMR

Compared 10% of the time

Amazon Redshift vs Amazon EMR

Compared 10% of the time

Spark SQL vs Amazon EMR

Compared 4% of the time

More Amazon EMR Competitors

Cloudera Distribution for Hadoop vs HPE Data Fabric

Compared 42% of the time

Cloudera Data Platform vs HPE Data Fabric

Compared 15% of the time

Apache Spark vs HPE Data Fabric

Compared 13% of the time

IBM Analytics Engine vs HPE Data Fabric

Compared 9% of the time

Spark SQL vs HPE Data Fabric

Compared 6% of the time

More HPE Data Fabric Competitors

Product Reports

Buyer's Guide

Amazon EMR

October 2025

Download Amazon EMR product report

Buyer's Guide

HPE Data Fabric

October 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

September 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: September 2025.

DOWNLOAD NOW

872,655 professionals have used our research since 2012.

See our Amazon EMR vs. HPE Data Fabric report.

See our list of best Hadoop vendors.

We monitor all Hadoop reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.