Amazon EMR vs HPE Data Fabric comparison

Why PeerSpot?

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 8.0, while Hewlett Packard Enterprise is ranked #5. Amazon Web Services (AWS) holds a 9.8% mindshare in H, compared to Hewlett Packard Enterprise’s 9.2% 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

4,458 Views
1,962 Comparison Views

83% willing to recommend

HPE Data Fabric

Read 12 HPE Data Fabric reviews

2,863 Views
2,376 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: November 2026).

Buyer's Guide

Amazon EMR vs. HPE Data Fabric

November 2026

Download the complete report

Helped 920,929 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

5th

Average Rating

8.0

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of November 2026, in the Hadoop category, the mindshare of Amazon EMR is 9.8%, down from 13.2% compared to the previous year. The mindshare of HPE Data Fabric is 9.2%, down from 14.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Hadoop Mindshare Distribution
Product	Mindshare (%)
Amazon EMR	9.8%
HPE Data Fabric	9.2%
Other	81.0%

Hadoop

Featured Reviews

reviewer2043696

Senior Technical Engineer at a transportation company with 5,001-10,000 employees

Data pipelines have simplified complex transformations and provide faster insights for users

The features at Amazon EMR that I have found most valuable are fully customizable functions. I am using Amazon EMR for data transformation, where we load the data. The entire ETL process is encompassed within it. The first thing is the egress part, where we pull the data from various sources, which include our main core databases, the systems that include Oracle, MySQL, SQL Server, and Postgres. We bring data from all these sources and use Amazon EMR specifically to combine all this data, clean the data, and combine it at a particular level. We bring everything to a particular level to make it more production-ready, and we simplify the data because every system has its own problems. We are using it to clean the data and transform the data in such a way that the end-user can get the insights faster.

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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.

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

"The solution is pretty simple to set up."

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

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

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

"The initial setup is pretty straightforward."

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

"It's easier to have everything connected via Amazon."

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

More Amazon EMR pros

"The fact that the heavy computation is required on Big Data can be distributed across many nodes in a cluster, makes this solution a winner."

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

"This product enabled us opening up endless possibilities in data analytics, IOE/IOT, and predictive analysis."

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

"Our customer purchased a paid support service and so far MapR has addressed our issues well."

"MapR is a great distribution, although I have limited experience with other distributors."

"I like the administration part."

"Outside of human error, MapR is probably the most stable of the major releases."

More HPE Data Fabric pros

Cons

"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."

"One of the lacking features is good web support."

"The problem for us is it starts very slow; they need to improve the start time."

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

"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 initial setup was time-consuming, and deployment took approximately 30 minutes."

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

"Whenever we have scaling policies for load balancing and our load increases the input rate, we increase the resources. However, at that time Amazon AWS is not providing the scale of the required resources in a short time."

More Amazon EMR cons

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

"The UI for administration still has a lot of manual work to set up the cluster and get it running."

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

"The product is not user-friendly."

"I'd say we've had issues with pricing."

"Installations and setups are still a bit cryptic and can be improved."

"The biggest drawback is that it has vendor locking."

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

More HPE Data Fabric cons

Pricing and Cost Advice

"The cost of Amazon EMR is very high."

"The price of the solution is expensive."

"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."

"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."

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

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

"Amazon EMR's price is reasonable."

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

15%

Manufacturing Company

10%

Construction Company

Healthcare Company

Construction Company

17%

Financial Services Firm

15%

Comms Service Provider

10%

Healthcare Company

10%

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

Snowflake vs Amazon EMR

Compared 7% of the time

Cloudera Distribution for Hadoop vs Amazon EMR

Compared 7% of the time

Apache Spark vs Amazon EMR

Compared 6% of the time

Amazon Redshift vs Amazon EMR

Compared 6% of the time

IBM Analytics Engine vs Amazon EMR

Compared 5% of the time

More Amazon EMR Competitors

Cloudera Distribution for Hadoop vs HPE Data Fabric

Compared 17% of the time

IBM Spectrum Computing vs HPE Data Fabric

Compared 11% of the time

IBM Analytics Engine vs HPE Data Fabric

Compared 11% of the time

Zettaset Data Platform vs HPE Data Fabric

Compared 9% of the time

Cloudera Data Platform vs HPE Data Fabric

Compared 9% of the time

More HPE Data Fabric Competitors

Product Reports

Buyer's Guide

Amazon EMR

October 2026

Download Amazon EMR product report

Buyer's Guide

HPE Data Fabric

October 2026

Download HPE Data Fabric product report

Also Known As

Amazon Elastic MapReduce

MapR, MapR Data Platform

Overview

Amazon EMR simplifies big data processing by offering integration with popular tools. It's scalable and cost-efficient, enabling fast processing while managing infrastructure effortlessly. It's designed for users aiming to streamline data workflows and leverage its batch processing capabilities effectively.

Amazon EMR is a managed service that provides robust features for big data processing. It integrates seamlessly with S3, EC2, Hive, and Spark to facilitate sophisticated data transformation tasks and infrastructure management. It allows organizations to run data lakes, Spark, and Hadoop clusters effortlessly, offering flexibility with on-demand execution and extensive scalability. The platform is valued for its strong processing speed and comprehensive security features, making it ideal for complex data engineering projects. It supports both batch processing and real-time workflows, designed to eliminate hardware management while maintaining cost efficiency and stability.

What are the key features of Amazon EMR?

Cluster Management: Offers intuitive control and configuration of clusters
Integration: Seamlessly integrates with S3, EC2, Spark, and more
Scalability: Provides flexible scaling to meet data demands
Batch Processing: Allows efficient handling of large data sets
Cost Efficiency: Minimizes costs with managed service offerings

What benefits and ROI should be considered?

Processing Speed: Fast performance for data processing tasks
Security: Built-in features ensure data protection
Infrastructure Simplification: Eliminates hardware management needs
Flexibility: Adapts to changing data loads with ease
Affordability: Offers economic processing power

Amazon EMR is implemented by industries such as healthcare and tech processing for complex data tasks like building data lakes or financial data processing. It supports AI-driven analytics and data engineering projects, integrating with SageMaker for predictions and maintaining workflows in public health applications, allowing professionals in different fields to manage data pipelines, resource utilization, and job execution efficiently.

Amazon Web Services (AWS)

HPE Data Fabric delivers robust data management with features like multi-tenancy, security, and ease of configuration. It supports high performance and unified analytics, making it a reliable choice for organizations looking to manage extensive data efficiently.

HPE Data Fabric provides a comprehensive data management platform with clustered node distribution and no single point of failure, ensuring high availability. Its compatibility with MapR-DB and NFS functionality allows integration with existing systems. Although there are challenges with third-party tool compatibility and upgrades, it supports big data initiatives by acting as both a database and messaging layer. Users benefit from bundled ecosystem support and simplified administration, enhancing usability across multiple teams and locations.

What features make HPE Data Fabric valuable?

Multi-tenancy: Supports multiple users or tenants securely.
Clustered Node Distribution: Distributes data across nodes for reliability.
POSIX Compliance: Compatibility with POSIX standards for ease of integration.
NFS Functionality: Facilitates network-based file sharing.
Unified Analytics: Provides integrated data analysis capabilities.

Why consider HPE Data Fabric in reviews?

Reliability: No single point of failure, ensuring consistent performance.
Cost Efficiency: Offers cost-effective data management solutions.
High Availability: Provides resilient storage and service availability.
Ease of Configuration: Streamlines administrative tasks with UI-driven tools.

Organizations in sectors such as finance, healthcare, and logistics use HPE Data Fabric to manage large volumes of data efficiently. Its role in supporting distributed processing and acting as a NoSQL storage solution enables these industries to leverage big data for enhanced operational insights and decision-making capabilities. The inclusion of AI tools further expands its utility, facilitating advanced data environments that are cost-effective and scalable for growing organizational demands.

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

November 2026

Free Report: Amazon EMR vs. HPE Data Fabric

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