HPE Ezmeral Data Fabric vs IBM Analytics Engine comparison

Hewlett Packard Enterprise and IBM are both solutions in the Hadoop category. Hewlett Packard Enterprise is ranked #4 with an average rating of 8.5, while IBM is ranked #10. Hewlett Packard Enterprise holds a 15.4% mindshare in H, compared to IBM’s 2.4% mindshare. Additionally, 100% of Hewlett Packard Enterprise users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

HPE Ezmeral Data Fabric

Read 12 HPE Ezmeral Data Fabric reviews

1,060 Views
558 Comparison Views

100% willing to recommend

IBM Analytics Engine

Read 1 IBM Analytics Engine review

153 Views
66 Comparison Views

100% willing to recommend

HPE Ezmeral Data Fabric

IBM Analytics Engine

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Executive Summary

We performed a comparison between HPE Ezmeral Data Fabric and IBM Analytics Engine based on real PeerSpot user reviews.

Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop.

To learn more, read our detailed Hadoop Report (Updated: June 2025).

Buyer's Guide

Hadoop

June 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

HPE Ezmeral 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

IBM Analytics Engine

Ranking in Hadoop

10th

Average Rating

8.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2025, in the Hadoop category, the mindshare of HPE Ezmeral Data Fabric is 15.4%, up from 11.8% compared to the previous year. The mindshare of IBM Analytics Engine is 2.4%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Hadoop

Featured Reviews

Hamid M. Hamid

Data architect at Banking Sector

A stable and scalable tool that serves as a great database

The initial setup of HPE Ezmeral Data Fabric is easy. I am not sure how long it took to deploy HPE Ezmeral Data Fabric, but I haven't heard about any disadvantages when it comes to the time taken for the deployment. I remember that one of our company's clients who had purchased the product never mentioned the product's setup phase being complex. One of the drawbacks with HPE Ezmeral Data Fabric stems from the fact that the product's upgrade was not straightforward, and it was a complex process since one of the teams in my company who deals with the tool found the upgrade part to be tough. The solution is deployed on an on-premises model. My company has two dedicated staff members to look after the deployment and maintenance phases of HPE Ezmeral Data Fabric.

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Saket Pandey

Product Manager at a hospitality company with 51-200 employees

Good solution for small and medium-sized businesses and highly stable

I would advise instead of only going through other reviews; it would be great if you could schedule a talk with the IBM team that would be helping you implement this solution. They would deep dive into the process and protocols you are currently set up in, and then they will provide you an optimal solution and optimal price. So I believe talking with the support team was really amazing. They even helped us in some other parts as well. It is a good solution for small and medium-sized businesses. Overall, I would rate the solution an eight out of ten because of the support team. They were able to resolve issues, which helped us deploy higher-grade solutions correctly and quickly. We were able to ensure that our processes were working correctly, and we saved about 15-16% of a week's time by using this solution. In terms of return on investment, we saved about $7,000 a month.

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

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

"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."

"I like the administration part."

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

"The best part was that we could make minor changes in the way we were bifurcating the data, even at a very small scale. The accuracy of conversion was also very high."

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 product is not user-friendly."

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

"One area for improvement would be the initial setup stage, which took longer than expected."

Pricing and Cost Advice

"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."

"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."

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

20%

Computer Software Company

15%

Comms Service Provider

Healthcare Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about HPE Ezmeral Data Fabric?

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

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What needs improvement with HPE Ezmeral Data Fabric?

There are some drawbacks in HPE Ezmeral Data Fabric when it comes to the interoperability part. HPE Ezmeral Data Fabric is not compatible with third-party tools. For example, HPE Ezmeral Data Fabri...

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What is your primary use case for HPE Ezmeral Data Fabric?

The main purpose of HPE Ezmeral Data Fabric for me is that it acts as a database. In my company, we store our data with the help of HPE Ezmeral Data Fabric. It is possible to use Spark engine with ...

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Comparisons

Cloudera Distribution for Hadoop vs HPE Ezmeral Data Fabric

Compared 55% of the time

Cloudera Data Platform vs HPE Ezmeral Data Fabric

Compared 10% of the time

Amazon EMR vs HPE Ezmeral Data Fabric

Compared 8% of the time

Spark SQL vs HPE Ezmeral Data Fabric

Compared 7% of the time

MongoDB vs HPE Ezmeral Data Fabric

Compared 6% of the time

More HPE Ezmeral Data Fabric Competitors

Spark SQL vs IBM Analytics Engine

Compared 50% of the time

More IBM Analytics Engine Competitors

Product Reports

Buyer's Guide

HPE Ezmeral Data Fabric

June 2025

Download HPE Ezmeral Data Fabric product report

Buyer's Guide

Hadoop

June 2025

Download IBM Analytics Engine product report

Also Known As

MapR, MapR Data Platform

No data available

Overview

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

IBM Analytics Engine provides an architecture for Hadoop clusters that decouples the compute and storage tiers. Instead of a permanent cluster formed of dual-purpose nodes, the Analytics Engine allows users to store data in an object storage layer such as IBM Cloud Object Storage and spins up clusters of compute notes when needed. Separating compute from storage helps to transform the flexibility, scalability and maintainability of big data analytics platforms.

IBM

Sample Customers

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

Information Not Available

Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop. Updated: June 2025.

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