Cloudera Distribution for Hadoop vs Spark SQL comparison

Cloudera and Apache are both solutions in the Hadoop category. Cloudera is ranked #2 with an average rating of 8.4, while Apache is ranked #5. Cloudera holds a 15.1% mindshare in H, compared to Apache’s 6.6% mindshare. Additionally, 92% of Cloudera users are willing to recommend the solution, compared to 86% of Apache users who would recommend it.

Cloudera Distribution for H...

Read 51 Cloudera Distribution for Hadoop reviews

1,935 Views
1,161 Comparison Views

92% willing to recommend

Spark SQL

Read 15 Spark SQL reviews

637 Views
554 Comparison Views

86% willing to recommend

Cloudera Distribution for H...

Spark SQL

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Executive Summary

We performed a comparison between Cloudera Distribution for Hadoop and Spark SQL based on real PeerSpot user reviews.

Find out in this report how the two Hadoop solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Cloudera Distribution for Hadoop vs. Spark SQL Report (Updated: December 2025).

Buyer's Guide

Cloudera Distribution for Hadoop vs. Spark SQL

December 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

Cloudera Distribution for H...

Ranking in Hadoop

2nd

Average Rating

8.0

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

NoSQL Databases (9th)

Spark SQL

Ranking in Hadoop

5th

Average Rating

7.8

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2026, in the Hadoop category, the mindshare of Cloudera Distribution for Hadoop is 15.1%, down from 27.9% compared to the previous year. The mindshare of Spark SQL is 6.6%, down from 10.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Hadoop Market Share Distribution
Product	Market Share (%)
Cloudera Distribution for Hadoop	15.1%
Spark SQL	6.6%
Other	78.3%

Hadoop

Featured Reviews

Rok Dolinsek

Manager, Bussines Development & Co Owner at Troia d.o.o.

Enables on-premise implementation with powerful data processing capabilities

This is the only solution that is possible to install on-premise. Cloudera provides a hybrid solution that combines compute on cloud or on-premises. It includes all machine learning algorithms in the Spark machine learning library. All functionalities needed for a big data platform and ETL are on the platform, eliminating the need for other tools. It is scalable, ready for vertical scaling, and very powerful, offering numerous functionalities and configurations for generative AI.

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Kemal Duman

Team Lead, Data Engineering at Nesine.com

Data pipelines have run faster and support flexible batch and streaming transformations

We do not have any performance problems, but we do have some resource problems. Spark SQL consumes so many resources that we migrated our streaming job from Spark to Apache Flink. Resource management in Spark SQL should be better. It consumes more resources, which is normal. The main reason we switched from Spark is memory and CPU consumption. The major reason is the resource problem because the number of streaming jobs has been increasing in our company. That is why we considered resource management as a priority. Because of the resource consumption, I would say the development of Spark SQL is better. For development purposes, it is a top product and not difficult to work with, but resources are the major problem. We changed to Flink regardless of development time. Development time is less in Spark compared with Flink.

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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

"Provides a viable open-source solution for enterprise implementations and reliable, intelligent data analysis."

"The search function is the most valuable aspect of the solution."

"The product is completely secure."

"I don't see any performance issues."

"The tool's most interesting features are the distributed file system and unstructured data processing capability. Because we have a lot of unstructured data, like XML and social media logs, these features make it more valuable than the usual data warehousing solutions."

"Cloudera Distribution for Hadoop provides numerous features and capabilities combined into one platform, offers power processing, supports different file systems and query engines, and provides parallel processing for handling many requests."

"The product provides better data processing features than other tools."

"The most valuable feature is Kubernetes."

More Cloudera Distribution for Hadoop pros

"Overall the solution is excellent."

"The team members don't have to learn a new language and can implement complex tasks very easily using only SQL."

"Spark SQL's efficiency in managing distributed data and its simplicity in expressing complex operations make it an essential part of our data pipeline."

"The speed of getting data."

"The stability was fine. It behaved as expected."

"It is a stable solution."

"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."

"This solution is useful to leverage within a distributed ecosystem."

More Spark SQL pros

Cons

"If they could support modifying the data more easily than the current implementation, it would be beneficial."

"The initial setup of Cloudera is difficult."

"The competitors provide better functionalities."

"The tool's ability to be deployed on a cloud model is an area of concern where improvements are required."

"The procedure for operations could be simplified."

"The dashboard could be improved."

"It is quite complicated to configure and install. Integrating the platform into an information system is always a challenge, especially when starting with on-premise implementation."

"The performance of some analytics engines provided by Cloudera is not that good."

More Cloudera Distribution for Hadoop cons

"It would be beneficial for aggregate functions to include a code block or toolbox that explains its calculations or supported conditional statements."

"In the next release, maybe the visualization of some command-line features could be added."

"I've experienced some incompatibilities when using the Delta Lake format."

"This solution could be improved by adding monitoring and integration for the EMR."

"The solution needs to include graphing capabilities. Including financial charts would help improve everything overall."

"There should be better integration with other solutions."

"In terms of improvement, the only thing that could be enhanced is the stability aspect of Spark SQL."

"In the next update, we'd like to see better performance for small points of data. It is possible but there are better tools that are faster and cheaper."

More Spark SQL cons

Pricing and Cost Advice

"I haven't bought a license for this solution. I'm only using the Apache license version."

"I wouldn't recommend CDH to others because of its high cost."

"The solution is fairly expensive."

"Cloudera Distribution for Hadoop is expensive, with support costs involved."

"I believe we pay for a three-year license."

"The price is very high. The solution is 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 could be better for the product."

More Cloudera Distribution for Hadoop pricing and cost advice

"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."

"The solution is bundled with Palantir Foundry at no extra charge."

"There is no license or subscription for this solution."

"The solution is open-sourced and free."

"We use the open-source version, so we do not have direct support from Apache."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

23%

Computer Software Company

Healthcare Company

Comms Service Provider

Financial Services Firm

16%

University

16%

Retailer

13%

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	16
Midsize Enterprise	9
Large Enterprise	31

By reviewers
Company Size	Count
Small Business	5
Midsize Enterprise	6
Large Enterprise	4

Questions from the Community

What do you like most about Cloudera Distribution for Hadoop?

The tool can be deployed using different container technologies, which makes it very scalable.

See all answers

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.

See all answers

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.

See all answers

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Comparisons

HPE Data Fabric vs Cloudera Distribution for Hadoop

Compared 15% of the time

MongoDB Enterprise Advanced vs Cloudera Distribution for Hadoop

Compared 11% of the time

Amazon EMR vs Cloudera Distribution for Hadoop

Compared 11% of the time

Couchbase Enterprise vs Cloudera Distribution for Hadoop

Compared 9% of the time

Apache Spark vs Cloudera Distribution for Hadoop

Compared 7% of the time

More Cloudera Distribution for Hadoop Competitors

Apache Spark vs Spark SQL

Compared 30% of the time

HPE Data Fabric vs Spark SQL

Compared 16% of the time

IBM Db2 Big SQL vs Spark SQL

Compared 15% of the time

SAP HANA vs Spark SQL

Compared 14% of the time

Amazon EMR vs Spark SQL

Compared 12% of the time

More Spark SQL Competitors

Product Reports

Buyer's Guide

Cloudera Distribution for Hadoop

January 2026

Download Cloudera Distribution for Hadoop product report

Buyer's Guide

Spark SQL

January 2026

Download Spark SQL product report

Overview

Cloudera Distribution for Hadoop is the world's most complete, tested, and popular distribution of Apache Hadoop and related projects. CDH is 100% Apache-licensed open source and is the only Hadoop solution to offer unified batch processing, interactive SQL, and interactive search, and role-based access controls. More enterprises have downloaded CDH than all other such distributions combined.

Cloudera

Spark SQL is a Spark module for structured data processing. Unlike the basic Spark RDD API, the interfaces provided by Spark SQL provide Spark with more information about the structure of both the data and the computation being performed. There are several ways to interact with Spark SQL including SQL and the Dataset API. When computing a result the same execution engine is used, independent of which API/language you are using to express the computation. This unification means that developers can easily switch back and forth between different APIs based on which provides the most natural way to express a given transformation.

Apache

Sample Customers

37signals, Adconion,adgooroo, Aggregate Knowledge, AMD, Apollo Group, Blackberry, Box, BT, CSC

UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, Hitachi Solutions

Buyer's Guide

Cloudera Distribution for Hadoop vs. Spark SQL

December 2025

Free Report: Cloudera Distribution for Hadoop vs. Spark SQL

Find out what your peers are saying about Cloudera Distribution for Hadoop vs. Spark SQL and other solutions. Updated: December 2025.

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