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 8.3, while Apache is ranked #5 with an average rating of 8.5. Cloudera holds a 25.0% mindshare in H, compared to Apache’s 9.8% 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 50 Cloudera Distribution for Hadoop reviews

1,644 Views
1,275 Comparison Views

92% willing to recommend

Spark SQL

Read 14 Spark SQL reviews

824 Views
603 Comparison Views

85% 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: March 2025).

Buyer's Guide

Cloudera Distribution for Hadoop vs. Spark SQL

March 2025

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Helped 845,406 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

2nd

Average Rating

8.0

Reviews Sentiment

6.4

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 April 2025, in the Hadoop category, the mindshare of Cloudera Distribution for Hadoop is 25.0%, up from 23.0% compared to the previous year. The mindshare of Spark SQL is 9.8%, down from 11.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

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

Sahil Taneja

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.

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

"We also really like the Cloudera community. You can have any question and will have your answer within a few hours."

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

"The solution's most valuable feature is the enterprise data platform."

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

"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 solution is stable."

"The most valuable feature is Kubernetes."

"I don't see any performance issues."

More Cloudera Distribution for Hadoop pros

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

"Overall the solution is excellent."

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

"Offers a variety of methods to design queries and incorporates the regular SQL syntax within tasks."

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

"The solution is easy to understand if you have basic knowledge of SQL commands."

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

More Spark SQL pros

Cons

"The procedure for operations could be simplified."

"It is quite complicated to configure and install."

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

"The solution is not fit for on-premise distributions."

"The price of this solution could be lowered."

"The tool doesn't support reporting, and relational databases are still the major source of reporting data. Apache Iceberg will be launched soon within the Cloudera cluster for analytical purposes. The Cloudera Machine Learning aspect could be tuned and enhanced to enable us to host some predictive analytics machine learning and AI use cases."

"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."

"The solution does not support multiple languages very well and this means users need to create work-arounds to implement some solutions."

More Cloudera Distribution for Hadoop cons

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

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

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

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

"There should be better integration with other solutions."

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

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

"It would be useful if Spark SQL integrated with some data visualization tools."

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."

"The price is very high. The solution is expensive."

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

"It is an expensive product."

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

"The tool is not expensive."

"The pricing must be improved."

"The solution is expensive."

More Cloudera Distribution for Hadoop pricing and cost advice

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

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

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

"The solution is open-sourced and free."

"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 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

25%

Computer Software Company

15%

Educational Organization

12%

Manufacturing Company

Financial Services Firm

22%

Computer Software Company

15%

Retailer

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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?

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. Integrating wit...

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 is your experience regarding pricing and costs for Spark SQL?

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.

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

Comparisons

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Neo4j Graph Database vs Cloudera Distribution for Hadoop

Compared 4% of the time

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Compared 4% of the time

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Apache Spark vs Spark SQL

Compared 50% of the time

SAP HANA vs Spark SQL

Compared 12% of the time

HPE Ezmeral Data Fabric vs Spark SQL

Compared 10% of the time

IBM Db2 Big SQL vs Spark SQL

Compared 10% of the time

Netezza Analytics vs Spark SQL

Compared 9% of the time

More Spark SQL Competitors

Product Reports

Buyer's Guide

Cloudera Distribution for Hadoop

March 2025

Download Cloudera Distribution for Hadoop product report

Buyer's Guide

Spark SQL

March 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

March 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: March 2025.

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