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Apache Spark vs Cloudera Distribution for Hadoop 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:
 

ROI

Sentiment score
7.3
Apache Spark reduces operational costs by up to 50%, offering high ROI and efficient performance despite infrastructure expenses.
Sentiment score
6.1
Assessing ROI from Cloudera for Hadoop varies, with significant value seen in 30 use cases across departments.
 

Customer Service

Sentiment score
6.1
Apache Spark support ranges from vibrant community help to paid vendor plans, with experiences varying based on user needs.
Sentiment score
6.7
Cloudera's customer support is praised for responsiveness and efficiency, despite occasional challenges with less experienced consultants.
The technical support is quite good and better than IBM.
 

Scalability Issues

Sentiment score
7.7
Apache Spark is scalable, efficiently manages large workloads, and is praised for stability, adaptability, and expansive capabilities.
Sentiment score
7.6
Cloudera Distribution for Hadoop is scalable, supporting large deployments and user bases despite challenges in cloud scalability and cost.
 

Stability Issues

Sentiment score
7.5
Apache Spark is stable and reliable, with improved versions addressing issues, widely used by major tech companies.
Sentiment score
7.5
Cloudera Distribution's stability is debated; some experience issues, while others find it reliable, rating it 8-10 out of 10.
 

Room For Improvement

Cloudera Distribution for Hadoop struggles with performance, integration, security, and cost, needing enhancements in multiple facets and technologies.
Integrating with Active Directory, managing security, and configuration are the main concerns.
 

Setup Cost

Cloudera Distribution for Hadoop is costly, complex, suitable for large enterprises, and offers a 60-day free trial.
It can be deployed on-premises, unlike competitors' cloud-only solutions.
 

Valuable Features

Cloudera Distribution for Hadoop excels with robust features, security, scalability, AI support, and strong community, surpassing competitors.
This is the only solution that is possible to install on-premise.
 

Categories and Ranking

Apache Spark
Ranking in Hadoop
1st
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
66
Ranking in other categories
Compute Service (4th), Java Frameworks (2nd)
Cloudera Distribution for H...
Ranking in Hadoop
2nd
Average Rating
8.0
Reviews Sentiment
6.4
Number of Reviews
50
Ranking in other categories
NoSQL Databases (8th)
 

Mindshare comparison

As of June 2025, in the Hadoop category, the mindshare of Apache Spark is 17.7%, down from 21.1% compared to the previous year. The mindshare of Cloudera Distribution for Hadoop is 25.5%, up from 24.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Hadoop
 

Featured Reviews

Dunstan Matekenya - PeerSpot reviewer
Open-source solution for data processing with portability
Apache Spark is known for its ease of use. Compared to other available data processing frameworks, it is user-friendly. While many choices now exist, Spark remains easy to use, particularly with Python. You can utilize familiar programming styles similar to Pandas in Python, including object-oriented programming. Another advantage is its portability. I can prototype and perform some initial tasks on my laptop using Spark without needing to be on Databricks or any cloud platform. I can transfer it to Databricks or other platforms, such as AWS. This flexibility allows me to improve processing even on my laptop. For instance, if I'm processing large amounts of data and find my laptop becoming slow, I can quickly switch to Spark. It handles small and large datasets efficiently, making it a versatile tool for various data processing needs.
Rok Dolinsek - PeerSpot reviewer
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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Top Industries

By visitors reading reviews
Financial Services Firm
27%
Computer Software Company
13%
Manufacturing Company
7%
Comms Service Provider
6%
Financial Services Firm
24%
Computer Software Company
14%
Educational Organization
14%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Apache Spark?
We use Spark to process data from different data sources.
What is your experience regarding pricing and costs for Apache Spark?
Apache Spark is open-source, so it doesn't incur any charges.
What needs improvement with Apache Spark?
There is complexity when it comes to understanding the whole ecosystem, especially for beginners. I find it quite complex to understand how a Spark job is initiated, the roles of driver nodes, work...
What do you like most about Cloudera Distribution for Hadoop?
The tool can be deployed using different container technologies, which makes it very scalable.
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.
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...
 

Overview

 

Sample Customers

NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
37signals, Adconion,adgooroo, Aggregate Knowledge, AMD, Apollo Group, Blackberry, Box, BT, CSC
Find out what your peers are saying about Apache Spark vs. Cloudera Distribution for Hadoop and other solutions. Updated: May 2025.
856,873 professionals have used our research since 2012.