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 25.7% mindshare in H, compared to Apache’s 10.5% 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: April 2025).

Buyer's Guide

Cloudera Distribution for Hadoop vs. Spark SQL

April 2025

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Helped 849,963 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 May 2025, in the Hadoop category, the mindshare of Cloudera Distribution for Hadoop is 25.7%, up from 24.2% compared to the previous year. The mindshare of Spark SQL is 10.5%, down from 12.1% 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.

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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 had a data warehouse before all the data. We can process a lot more data structures."

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

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

"Cloudera, as a whole, is designed to provide organizations with solutions for big data."

"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."

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

"The product as a whole is good."

"The most valuable feature is Kubernetes."

More Cloudera Distribution for Hadoop pros

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

"The performance is one of the most important features. It has an API to process the data in a functional manner."

"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."

"Overall the solution is excellent."

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

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

"I find the Thrift connection valuable."

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

More Spark SQL pros

Cons

"The dashboard could be improved."

"This is a very expensive solution."

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

"There is a maximum of a one-gigabyte block size, which is an area of storage that can be improved upon."

"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."

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

"Cloudera's support is extremely bad and cannot be relied on."

"It could be faster and more user-friendly."

More Cloudera Distribution for Hadoop cons

"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 should be better integration with other solutions."

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

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

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

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

"Anything to improve the GUI would be helpful."

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

More Spark SQL cons

Pricing and Cost Advice

"When comparing with Oracle Sybase and SQL, it's cheaper. It's not expensive."

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

"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."

"It is an expensive product."

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

"The tool is not expensive."

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

"The pricing must be improved."

More Cloudera Distribution for Hadoop pricing and cost advice

"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."

"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 solution is open-sourced and free."

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

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

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Top Industries

By visitors reading reviews

Financial Services Firm

25%

Computer Software Company

15%

Educational Organization

14%

Manufacturing Company

Financial Services Firm

22%

Computer Software Company

16%

Manufacturing Company

Retailer

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

HPE Ezmeral Data Fabric vs Cloudera Distribution for Hadoop

Compared 31% of the time

Amazon EMR vs Cloudera Distribution for Hadoop

Compared 29% of the time

Apache Spark vs Cloudera Distribution for Hadoop

Compared 17% of the time

Cassandra vs Cloudera Distribution for Hadoop

Compared 5% of the time

Neo4j Graph Database vs Cloudera Distribution for Hadoop

Compared 4% of the time

More Cloudera Distribution for Hadoop Competitors

Apache Spark vs Spark SQL

Compared 50% of the time

SAP HANA vs Spark SQL

Compared 14% of the time

HPE Ezmeral Data Fabric vs Spark SQL

Compared 13% of the time

IBM Db2 Big SQL vs Spark SQL

Compared 13% of the time

IBM Analytics Engine vs Spark SQL

Compared 10% of the time

More Spark SQL Competitors

Product Reports

Buyer's Guide

Cloudera Distribution for Hadoop

April 2025

Download Cloudera Distribution for Hadoop product report

Buyer's Guide

Spark SQL

April 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

April 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: April 2025.

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