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Cloudera Distribution for Hadoop vs HPE Data Fabric 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

Cloudera Distribution for H...
Ranking in Hadoop
2nd
Average Rating
8.0
Reviews Sentiment
6.3
Number of Reviews
51
Ranking in other categories
NoSQL Databases (12th)
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
 

Mindshare comparison

As of May 2026, in the Hadoop category, the mindshare of Cloudera Distribution for Hadoop is 14.8%, down from 25.8% compared to the previous year. The mindshare of HPE Data Fabric is 10.5%, down from 15.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Hadoop Mindshare Distribution
ProductMindshare (%)
Cloudera Distribution for Hadoop14.8%
HPE Data Fabric10.5%
Other74.7%
Hadoop
 

Featured Reviews

SA
Head of Advaced Analytics & Intelligence; AGM at Alinma Bank
Integration of multiple features supports data analytics and processing
Cloudera Distribution for Hadoop provides numerous features and capabilities combined into one platform.The solution offers power processing and supports different file systems and query engines. It provides parallel processing for handling many requests. The platform includes role-based access control in Cloudera Distribution for Hadoop. It secures the data itself and provides users with different roles and privileges.
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.

Quotes from Members

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

Pros

"CDH has a wide variety of proprietary tools that we use, like Impala. So from that perspective, it's quite useful as opposed to something open-source. We get a lot of value from Cloudera's proprietary tools."
"The solution is reliable and stable, it fits our requirements."
"Cloudera is a very manageable solution with good support."
"Cloudera really has no competition."
"Very good end-to-end security features."
"For the clusters using CM, we are able to more tightly control and manage the configuration of all nodes in the clusters."
"The most valuable feature is that I can use CDH for almost all use cases across all industries, including the financial sector, public sector, private retailers, and so on."
"We're now able to store large volumes of data through Cloudera Distribution for Hadoop. We're able to push large volumes of data to the platform, and that used to be a challenge, especially when storing a terabyte of information. This is the area where Cloudera Distribution for Hadoop improved the organization."
"The model creation was very interesting, especially with the libraries provided by the 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."
"This product enabled us opening up endless possibilities in data analytics, IOE/IOT, and predictive analysis."
"Initial setup is rather straightforward thanks to detailed documentation covering all the bases."
"It is a stable solution...It is a scalable solution."
"I highly recommend MapR."
"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 like the administration part."
 

Cons

"The user infrastructure and user interface needs to be improved, as well as the performance. The GUI needs to be better."
"Spark with R integration is missing. Also, it is lacking Spark SQL support."
"Cloudera Distribution for Hadoop has a limited feature list and a lot of costs involved."
"Cloudera Distribution for Hadoop has a limited feature list and a lot of costs involved."
"The Data Science Workbench doesn't support multiple languages. It needs to support multiple programming languages."
"This is a very expensive solution."
"We're currently trying to perform a failed installation and it's little bit difficult. It should restart the installation where it left off."
"We experienced many issues when we started working with Hadoop 3.0 in the Cloudera 6.0 version, so there are a lot of things that need to improve."
"The UI for administration still has a lot of manual work to set up the cluster and get it running."
"I'd say we've had issues with pricing."
"Having the ability to extend the services provided by the platform to an API architecture, a micro-services architecture, could be very helpful."
"Installations and setups are still a bit cryptic and can be improved."
"The interface part, what I'm calling the integration part, could be improved."
"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 biggest drawback is that it has vendor locking."
"One weakness for MapR is the Kerberos support."
 

Pricing and Cost Advice

"The solution is fairly expensive."
"The tool is expensive...For the SMB market or customers whose environments are not that complex and do not have multiple systems running, Cloudera might not be a good option."
"The price is very high. The solution is expensive."
"The solution is expensive."
"The pricing must be improved."
"I haven't bought a license for this solution. I'm only using the Apache license version."
"The tool is not expensive."
"I believe we pay for a three-year license."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
23%
Marketing Services Firm
9%
Comms Service Provider
6%
Healthcare Company
6%
Financial Services Firm
17%
Construction Company
11%
Comms Service Provider
9%
Healthcare Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business16
Midsize Enterprise9
Large Enterprise31
By reviewers
Company SizeCount
Small Business4
Large Enterprise7
 

Questions from the Community

What is your experience regarding pricing and costs for Cloudera Distribution for Hadoop?
The price for Cloudera is average, yet it is very good compared to other solutions. It can be deployed on-premises, unlike competitors' cloud-only solutions.
What needs improvement with Cloudera Distribution for Hadoop?
If they could support modifying the data more easily than the current implementation, it would be beneficial.
What is your primary use case for Cloudera Distribution for Hadoop?
We use Cloudera Distribution for Hadoop for many use cases including analytics, storing huge data sets, and various data processing tasks.
Ask a question
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Also Known As

No data available
MapR, MapR Data Platform
 

Overview

 

Sample Customers

37signals, Adconion,adgooroo, Aggregate Knowledge, AMD, Apollo Group, Blackberry, Box, BT, CSC
Valence Health, Goodgame Studios, Pico, Terbium Labs, sovrn, Harte Hanks, Quantium, Razorsight, Novartis, Experian, Dentsu ix, Pontis Transitions, DataSong, Return Path, RAPP, HP
Find out what your peers are saying about Cloudera Distribution for Hadoop vs. HPE Data Fabric and other solutions. Updated: April 2026.
893,244 professionals have used our research since 2012.