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HPE Data Fabric vs IBM Spectrum Computing comparison

 

Comparison Buyer's Guide

Executive Summary

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 Data Fabric
Ranking in Hadoop
4th
Average Rating
8.0
Reviews Sentiment
6.1
Number of Reviews
12
Ranking in other categories
No ranking in other categories
IBM Spectrum Computing
Ranking in Hadoop
7th
Average Rating
7.8
Reviews Sentiment
5.9
Number of Reviews
9
Ranking in other categories
Cloud Management (27th)
 

Mindshare comparison

As of April 2026, in the Hadoop category, the mindshare of HPE Data Fabric is 11.6%, down from 15.3% compared to the previous year. The mindshare of IBM Spectrum Computing is 5.2%, up from 1.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Hadoop Mindshare Distribution
ProductMindshare (%)
HPE Data Fabric11.6%
IBM Spectrum Computing5.2%
Other83.2%
Hadoop
 

Featured Reviews

Hamid M. Hamid - PeerSpot reviewer
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.
OmarIsmail1 - PeerSpot reviewer
Infrastructure Technical Specialist II at Clicks Group
Senior Technical Specialist appreciates intelligent workload management, strong support, and scalability
The best features of IBM Spectrum Computing are common across many of their storage products. The software is solid, meaning that the code is stable. They take business seriously, which is what IBM stands for - International Business Machines. They always maintain a business-oriented approach in their software development. It's not simply clicking through interfaces; in IBM software, they consider their actions, process flows, and workflows around business processes. It requires understanding IBM and their methodology, as the software operates accordingly. I have utilized IBM Spectrum Computing's intelligent workload management feature. We use Insights, which is connected to the cloud. This provides AI capabilities for analyzing the configuration, offering smart recommendations on new code, warning about bugs in current code, and suggesting configuration improvements through its advisor tool. The predictive analytics feature in IBM Spectrum Computing enables optimal software performance through Insights. However, being a storage administrator requires foundational knowledge and understanding beyond these tools. For troubleshooting, it's efficient in spotting bottlenecks, but understanding the terms and metrics is essential as it provides answers that need interpretation.

Quotes from Members

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

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."
"I highly recommend MapR."
"My first choice is MapR, as it is more adaptable to different contexts, and it could be customized in some way to fit the different needs, and this is my first choice and my first advice to people who ask me about this particular platform."
"MapR is a great distribution, although I have limited experience with other distributors."
"Our customer purchased a paid support service and so far MapR has addressed our issues well."
"Initial setup is rather straightforward thanks to detailed documentation covering all the bases."
"It is a stable solution...It is a scalable solution."
"I like the administration part."
"The comparison was challenging, but the IBM Spectrum Scale offered a balanced solution. Our engineers rated itsanalytics capabilities equally high as Pure Storage. For workload management, Spectrum Computing provided effective solutions that met our needs. Workload management is part of a complete solution that uses different tools. There were the cloud and HPC parts; within HPC, there were parts like liquid cooling, simple computing, storage, and orchestration. The orchestration team handled the workload management."
"This solution is working for both VTL and tape."
"Spectrum Computing's best features are its speed, robustness, and data processing and analysis."
"I have utilized IBM Spectrum Computing's intelligent workload management feature through Insights, which is connected to the cloud."
"IBM's ability to cluster compute resources is impressive, with built-in support for scenarios like VR and active-active configurations,"
"This solution worked as expected and it is reliable."
"I tell everyone that they should go with IBM Spectrum Computing."
"Easy to operate and use."
 

Cons

"Installations and setups are still a bit cryptic and can be improved."
"It would be nice to have new developments in the Apache space (Spark, Storm, etc.)."
"HPE Ezmeral Data Fabric is not compatible with third-party tools."
"The interface part, what I'm calling the integration part, could be improved."
"It'd like to see file system auditing, data encryption, and certification of other vendors' tools."
"The deployment could be faster. I want more support for the data lake in the next release."
"I'd say we've had issues with pricing."
"One weakness for MapR is the Kerberos support."
"Lack of sufficient documentation, particularly in Spanish."
"SMB storage and HPC is not compatible and it should be supported by IBM Spectrum Computing."
"We have not been able to use deduplication."
"In Pakistan, IBM's disadvantage is the lack of OEM support and presence."
"We'd like to see some AI model training for machine learning."
"We are not fully satisfied with this product at the moment because we are having issues with reliability."
"The deduplication software isn't quite up to speed with the market."
"Software sometimes is a little slower. It takes two or three days sometimes."
 

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."
"This solution is expensive."
"Spectrum Computing is one of the most expensive products on the market."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Construction Company
11%
Healthcare Company
10%
Comms Service Provider
8%
Financial Services Firm
16%
Manufacturing Company
14%
Construction Company
10%
Outsourcing Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Large Enterprise7
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise1
Large Enterprise6
 

Questions from the Community

Ask a question
Earn 20 points
What is your experience regarding pricing and costs for IBM Spectrum Computing?
IBM Spectrum Computing consistently offers competitive pricing. When solutioning new implementations, IBM always presents the best solution and price. In a recent comparison with Pure Storage and N...
What needs improvement with IBM Spectrum Computing?
IBM Spectrum Computing had limitations with remote copy services between head office and disaster recovery sites. In the last year, IBM has improved the code by re-engineering it to policy-based re...
What is your primary use case for IBM Spectrum Computing?
The typical use case for IBM Spectrum Computing is that it's an all-rounder. It can be used in various scenarios, such as the retailer I work for that has batch processing. It's on-demand when perf...
 

Also Known As

MapR, MapR Data Platform
IBM Platform Computing
 

Overview

 

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
London South Bank University, Transvalor, Infiniti Red Bull Racing, Genomic
Find out what your peers are saying about HPE Data Fabric vs. IBM Spectrum Computing and other solutions. Updated: April 2026.
890,088 professionals have used our research since 2012.