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HPE Data Fabric vs IBM Netezza Performance Server comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Mar 1, 2026

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 Netezza Performance Server
Ranking in Hadoop
6th
Average Rating
7.8
Reviews Sentiment
6.9
Number of Reviews
45
Ranking in other categories
Data Warehouse (11th)
 

Mindshare comparison

As of October 2026, in the Hadoop category, the mindshare of HPE Data Fabric is 9.3%, down from 14.4% compared to the previous year. The mindshare of IBM Netezza Performance Server is 6.0%, up from 1.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Hadoop Mindshare Distribution
ProductMindshare (%)
HPE Data Fabric9.3%
IBM Netezza Performance Server6.0%
Other84.7%
Hadoop
 

Featured Reviews

Arnab Chatterjee - PeerSpot reviewer
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.
Shiv Subramaniam Koduvayur - PeerSpot reviewer
Project Manager at MAF Retail
Parallel data processing streamlines operations while cost and cloud integration challenge adoption
The cost of the solution is on the more expensive side, which is a concern for me. Additionally, its promotion and interaction with cloud applications are limited. The cloud version is only available in AWS, and in the Middle East, it is not well-developed in the Azure environment. For the cost to be reduced, it should match competitors. Many features need to be incorporated on the cloud.

Quotes from Members

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

Pros

"I like the administration part."
"HPE Ezmeral Data Fabric can be accessed from any namespace globally as you would access it from a machine using an NFS."
"Initial setup is rather straightforward thanks to detailed documentation covering all the bases."
"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."
"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."
"The model creation was very interesting, especially with the libraries provided by the platform."
"Outside of human error, MapR is probably the most stable of the major releases."
"Distribution (no index or partition), built-in analytics is a major advantange."
"The underlying hardware that IBM provides with this appliance is made for a specific purpose, to serve performance on a large amount of data, and to do analytics as well. It is faster, when you compare it to any other product."
"ARULES() function is the fastest implementation of the associations algorithm (a priori or tree) I have worked with, and in comparison with the R associations package, it is +1000x faster."
"For me, as an end-user, everything that I do on the solution is simple, clear, and understandable."
"The most valuable features of the IBM Netezza Performance Server are the NPS server because of the reduced maintenance and overall good performance."
"For every organization that I have been in that has Netezza, the ability to load and run queries is greatly simplified and A LOT faster than any other DBMS out there."
"The performance is most important to me, and it helps our ability to make business decisions quickly."
"Earlier there was high latency to query extraction but Netezza has improved the speed for all OLAP operations, helping the organization get business answers right on time."
 

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."
"I'd say we've had issues with pricing."
"The biggest drawback is that it has vendor locking."
"The UI for administration still has a lot of manual work to set up the cluster and get it running."
"The product is not user-friendly."
"One weakness for MapR is the Kerberos support."
"Having the ability to extend the services provided by the platform to an API architecture, a micro-services architecture, could be very helpful."
"It would be nice to have new developments in the Apache space (Spark, Storm, etc.)."
"Community support. There was none, or very little, especially when using add-on software (e.g. building functions, MapReduce, R, Lua, etc.)."
"We are not able to scale. The only way to scale is to get another appliance, but we have a customers who would need us to hydrate the data between the two appliances, and Netezza does not do that."
"Application development in Netezza is done using SQL scripts and stored procedures."
"LIke Teradata, we can’t add a node/SPU to the existing appliance."
"The hardware has a risk of failure. They need to improve this."
"We found some bugs - boundary conditions mostly."
"Scalability of this solution is not possible."
"The only issue is that it's not expandable."
 

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."
"Netezza is a costly solution. It does serve a specific purpose but it's costlier than what's available in the market, if you go to the cloud."
"The annual licensing fees are twenty-two percent of the product cost."
"For me, mainly, it reduces my costs. It's not only the appliance cost. There are also support costs and a maintenance costs. It does reduce the costs very drastically."
"Expensive to maintain compared to other solutions."
"The solution has a yearly licensing fee, and users have to pay extra for support."
"The pricing is very expensive. It has a lot CPUs with a lot of components in it. It also has built-in redundancy for resiliency reasons."
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Comparison Review

it_user232068 - PeerSpot reviewer
Senior Data Architect at a pharma/biotech company with 1,001-5,000 employees
Aug 5, 2015
Netezza vs. Teradata
Original published at https://www.linkedin.com/pulse/should-i-choose-net Two leading Massively Parallel Processing (MPP) architectures for Data Warehousing (DW) are IBM PureData System for Analytics (formerly Netezza) and Teradata. I thought talking about the similarities and differences…
 

Top Industries

By visitors reading reviews
Construction Company
17%
Financial Services Firm
16%
Healthcare Company
10%
Comms Service Provider
9%
Outsourcing Company
15%
Financial Services Firm
15%
Comms Service Provider
10%
Manufacturing Company
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Large Enterprise7
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise6
Large Enterprise33
 

Questions from the Community

Ask a question
Earn 20 points
What needs improvement with IBM Netezza Performance Server?
The cost of the solution is on the more expensive side, which is a concern for me. Additionally, its promotion and interaction with cloud applications are limited. The cloud version is only availab...
What advice do you have for others considering IBM Netezza Performance Server?
The solution has generally received positive feedback from me and is recommended for continued use by end users. However, the product cost is high compared to others in the market, and this cost ha...
 

Also Known As

MapR, MapR Data Platform
Netezza Performance Server, Netezza, Netezza Analytics
 

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
Seattle Childrens Hospital, Carphone Warehouse, Vanderbilt University School of Medicine, Battelle, Start Today Co. Ltd., Kelley Blue Book, Trident Marketing, Elisa Corporation, Catalina Marketing, iBasis, Barnes & Noble, Qualcomm, MediaMath, Acxiom, iBasis, Foxwoods
Find out what your peers are saying about HPE Data Fabric vs. IBM Netezza Performance Server and other solutions. Updated: September 2026.
917,433 professionals have used our research since 2012.