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HPE Data Fabric vs Spark SQL 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
3rd
Average Rating
8.0
Reviews Sentiment
6.1
Number of Reviews
12
Ranking in other categories
No ranking in other categories
Spark SQL
Ranking in Hadoop
5th
Average Rating
7.8
Reviews Sentiment
7.6
Number of Reviews
14
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of December 2025, in the Hadoop category, the mindshare of HPE Data Fabric is 15.2%, up from 14.0% compared to the previous year. The mindshare of Spark SQL is 7.4%, down from 9.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Hadoop Market Share Distribution
ProductMarket Share (%)
HPE Data Fabric15.2%
Spark SQL7.4%
Other77.4%
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.
Sahil Taneja - PeerSpot reviewer
Principal Consultant/Manager at Tenzing
Easy to use and do not require a learning curve
Spark SQL can improve the documentation they have provided. It can be a bit unclear at times. They could improve the documentation a bit more so that we can understand it more easily. Moreover, they could improve SparkUI to have more advanced versions of the performance and the queries and all.

Quotes from Members

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

Pros

"It is a stable solution...It is a scalable solution."
"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."
"HPE Ezmeral Data Fabric can be accessed from any namespace globally as you would access it from a machine using an NFS."
"The model creation was very interesting, especially with the libraries provided by the platform."
"I like the administration part."
"Data validation and ease of use are the most valuable features."
"Offers a variety of methods to design queries and incorporates the regular SQL syntax within tasks."
"I find the Thrift connection valuable."
"Spark SQL's efficiency in managing distributed data and its simplicity in expressing complex operations make it an essential part of our data pipeline."
"Certain data sets that are very large are very difficult to process with Pandas and Python libraries. Spark SQL has helped us a lot with that."
"One of Spark SQL's most beautiful features is running parallel queries to go through enormous data."
"This solution is useful to leverage within a distributed ecosystem."
"The solution is easy to understand if you have basic knowledge of SQL commands."
 

Cons

"Having the ability to extend the services provided by the platform to an API architecture, a micro-services architecture, could be very helpful."
"HPE Ezmeral Data Fabric is not compatible with third-party tools."
"The product is not user-friendly."
"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."
"It would be beneficial for aggregate functions to include a code block or toolbox that explains its calculations or supported conditional statements."
"It would be useful if Spark SQL integrated with some data visualization tools."
"I've experienced some incompatibilities when using the Delta Lake format."
"Being a new user, I am not able to find out how to partition it correctly. I probably need more information or knowledge. In other database solutions, you can easily optimize all partitions. I haven't found a quicker way to do that in Spark SQL. It would be good if you don't need a partition here, and the system automatically partitions in the best way. They can also provide more educational resources for new users."
"It takes a bit of time to get used to using this solution versus Pandas as it has a steep learning curve."
"This solution could be improved by adding monitoring and integration for the EMR."
"In terms of improvement, the only thing that could be enhanced is the stability aspect of Spark SQL."
"Anything to improve the GUI would be helpful."
 

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."
"The solution is bundled with Palantir Foundry at no extra charge."
"The on-premise solution is quite expensive in terms of hardware, setting up the cluster, memory, hardware and resources. It depends on the use case, but in our case with a shared cluster which is quite large, it is quite expensive."
"We use the open-source version, so we do not have direct support from Apache."
"The solution is open-sourced and free."
"There is no license or subscription for this solution."
"We don't have to pay for licenses with this solution because we are working in a small market, and we rely on open-source because the budgets of projects are very small."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
9%
Comms Service Provider
8%
Construction Company
7%
Financial Services Firm
16%
University
14%
Retailer
11%
Manufacturing 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 Business5
Midsize Enterprise5
Large Enterprise4
 

Also Known As

MapR, MapR Data Platform
No data available
 

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
UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, Hitachi Solutions
Find out what your peers are saying about HPE Data Fabric vs. Spark SQL and other solutions. Updated: December 2025.
879,371 professionals have used our research since 2012.