Cloudera Distribution for Hadoop vs Spark SQL comparison

Cloudera and Apache are both solutions in the Hadoop category. Cloudera is ranked #1 with an average rating of 8.2, while Apache is ranked #5 with an average rating of 7.0. Cloudera holds a 21.9% mindshare in H, compared to Apache’s 9.4% mindshare. Additionally, 92% of Cloudera users are willing to recommend the solution, compared to 85% of Apache users who would recommend it.

Cloudera Distribution for H...

Read 51 Cloudera Distribution for Hadoop reviews

1,737 Views
1,112 Comparison Views

92% willing to recommend

Spark SQL

Read 14 Spark SQL reviews

593 Views
522 Comparison Views

85% willing to recommend

Cloudera Distribution for H...

Spark SQL

Comparison Buyer's Guide

Download the report

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: September 2025).

Buyer's Guide

Cloudera Distribution for Hadoop vs. Spark SQL

September 2025

Download the complete report

Helped 869,566 peers since 2012

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

1st

Average Rating

8.0

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

NoSQL Databases (8th)

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 October 2025, in the Hadoop category, the mindshare of Cloudera Distribution for Hadoop is 21.9%, down from 26.4% compared to the previous year. The mindshare of Spark SQL is 9.4%, down from 10.1% 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	21.9%
Spark SQL	9.4%
Other	68.7%

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.

Read full review

SurjitChoudhury

Data engineer at Cocos pt

Offers the flexibility to handle large-scale data processing

My experience with the initial setup of Spark SQL was relatively smooth. Understanding the system wasn't overly difficult because the data was structured in databases, and we could use notebooks for coding in Python or Java. Configuring networks and running scripts to load data into the database were routine tasks that didn't pose significant challenges. The flexibility to use different languages for coding and the ability to process data using key-value pairs in Python made the setup adaptable. Once we received the source data, processing it in SparkSQL involved writing scripts to create dimension and fact tables, which became a standard part of our workflow. Setting up Spark SQL was reasonably quick, but sometimes we face performance issues, especially during data loading into the SQL Server data warehouse. Sequencing notebooks for efficient job runs is crucial, and managing complex tasks with multiple notebooks requires careful tracking. Exploring ways to optimize this process could be beneficial. However, once you are familiar with the database architecture and project tools, understanding and adapting to the system become more straightforward.

Read full review

Quotes from Members

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

Pros

"Very good end-to-end security features."

"The main advantage is the storage is less expensive."

"The solution is stable."

"This is the only solution that is possible to install on-premise."

"It is helpful to gather and process data."

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

"The features I find most valuable is that the solution is that it is easy to install and to work with. It starts with the installation and from there on the management is very simple and centralized."

"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."

More Cloudera Distribution for Hadoop pros

"One of Spark SQL's most beautiful features is running parallel queries to go through enormous data."

"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."

"The speed of getting data."

"I find the Thrift connection valuable."

"Overall the solution is excellent."

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

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

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

More Spark SQL pros

Cons

"The one thing that we struggled with predominately was support. Because it was relatively new, support was always a big issue and I think it's still a bit of an ongoing concern with the team currently managing it."

"Currently, we are using many other tools such as Spark and Blade Job to improve the performance."

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

"It is quite complicated to configure and install."

"We experienced many issues when we started working with Hadoop 3.0 in the Cloudera 6.0 version, so there is a lot of things that need to improve."

"The security of this solution could be improved. There should also be a way to basically have a blockchain enabled storage with the HDFS."

"It would be useful if Cloudera had more tools like SQL Engines that offer the traditional relational database. We have to do a lot of work preparing the data outside Cloudera before getting it into the platform."

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

More Cloudera Distribution for Hadoop cons

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

"SparkUI could have more advanced versions of the performance and the queries and all."

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

"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."

"There are many inconsistencies in syntax for the different querying tasks."

"It takes a bit of time to get used to using this solution versus Pandas as it has a steep learning curve."

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

"There should be better integration with other solutions."

More Spark SQL cons

Pricing and Cost Advice

"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."

"Cloudera requires a license to use."

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

"The product’s price depends from project to project."

"The tool is not expensive."

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

"The pricing must be improved."

"It is an expensive product."

More Cloudera Distribution for Hadoop pricing and cost advice

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

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

"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 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."

See which vendors are best for you

Use our free recommendation engine to learn which Hadoop solutions are best for your needs.

See recommendations

869,566 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Educational Organization

18%

Financial Services Firm

18%

Computer Software Company

11%

Energy/Utilities Company

Financial Services Firm

17%

University

12%

Retailer

11%

Manufacturing 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	5
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

What do you like most about Spark 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.

See all answers

What needs improvement with Spark SQL?

In terms of improvement, the only thing that could be enhanced is the stability aspect of Spark SQL. There could be additional features that I haven't explored but the current solution for working ...

See all answers

What is your primary use case for Spark SQL?

I employ Spark SQL for various tasks. Initially, I gathered data from databases, SAP systems, and external sources via SFTP, storing it in blob storage. Using Spark SQL within Jupyter notebooks, I ...

See all answers

Comparisons

HPE Ezmeral Data Fabric vs Cloudera Distribution for Hadoop

Compared 24% of the time

Amazon EMR vs Cloudera Distribution for Hadoop

Compared 21% of the time

MongoDB Enterprise Advanced vs Cloudera Distribution for Hadoop

Compared 13% of the time

Couchbase Enterprise vs Cloudera Distribution for Hadoop

Compared 13% of the time

Apache Spark vs Cloudera Distribution for Hadoop

Compared 10% of the time

More Cloudera Distribution for Hadoop Competitors

Apache Spark vs Spark SQL

Compared 62% of the time

SAP HANA vs Spark SQL

Compared 21% of the time

Amazon EMR vs Spark SQL

Compared 17% of the time

More Spark SQL Competitors

Product Reports

Buyer's Guide

Cloudera Distribution for Hadoop

October 2025

Download Cloudera Distribution for Hadoop product report

Buyer's Guide

Spark SQL

September 2025

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

September 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: September 2025.

DOWNLOAD NOW

869,566 professionals have used our research since 2012.

See our Cloudera Distribution for Hadoop vs. Spark SQL report.

See our list of best Hadoop vendors.

We monitor all Hadoop reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.