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Apache Spark vs Cloudera Data Platform comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Apr 1, 2025

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
5.6
Users experience varied ROI from Cloudera Data Platform, with outcomes depending on deployment specifics and infrastructure usage.
 

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 support is generally helpful but varies, with paid services rated better; interaction with engineers is highly valued.
I have communicated with technical support, and they are responsive and helpful.
 

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
6.6
Cloudera Data Platform is highly scalable and efficient, outperforming Hortonworks despite minor upgrade challenges that are manageable with support.
Integration with other tools works well for us and we successfully scaled the solution after two to three years without any issues.
For scalability, I rate Cloudera Data Platform at an eight out of ten as it is an on-premise solution.
 

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
7.1
Cloudera Data Platform is stable with minimal issues, mostly related to hardware or updates, and is highly rated for reliability.
 

Room For Improvement

Cloudera Data Platform needs improvements in usability, security, cloud integration, cost, and support for broader industry application.
We aim to address these issues with a Kubernetes-based platform that will simplify the task of upgrading services.
Cloudera Data Platform should include additional capabilities and features similar to those offered by other data management solutions like Azure and Databricks.
 

Setup Cost

Cloudera Data Platform's pricing is complex yet affordable, valued for open-source aspects and professional service needs for optimization.
Initially, CDH had a straightforward pricing model based on nodes, but CDP includes factors like processors, cores, terabytes, and drives, making it difficult to calculate costs.
 

Valuable Features

Cloudera Data Platform excels in flexibility, scalability, and comprehensive features for efficient data management, secure containerization, and AI support.
By using the Hadoop File System for distributed storage, we have 1.5 petabytes of physical storage with 500 terabytes of effective storage due to a replication factor of three.
The foremost benefit is offloading data from the warehouse to Cloudera Data Platform, which allows for cheaper storage.
 

Categories and Ranking

Apache Spark
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
66
Ranking in other categories
Hadoop (1st), Compute Service (4th), Java Frameworks (2nd)
Cloudera Data Platform
Average Rating
8.0
Reviews Sentiment
6.4
Number of Reviews
27
Ranking in other categories
Cloud Master Data Management (MDM) Solutions (7th), Data Management Platforms (DMP) (4th)
 

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.
Miodrag-Stanic - PeerSpot reviewer
Distributed computing improves data processing while upgrade complexity needs addressing
There are challenges with upgrading or updating various services like Spark, Impala, and Hive on on-premise and bare metal solutions. We aim to address these issues with a Kubernetes-based platform that will simplify the task of upgrading services. We also wish to implement lakehouse capabilities with Iceberg or Delta Lake frameworks.
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Top Industries

By visitors reading reviews
Financial Services Firm
27%
Computer Software Company
12%
Manufacturing Company
7%
Comms Service Provider
6%
Financial Services Firm
14%
Real Estate/Law Firm
12%
Computer Software Company
10%
Performing Arts
8%
 

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 Hortonworks Data Platform?
Distributed computing, secure containerization, and governance capabilities are the most valuable features.
What is your experience regarding pricing and costs for Hortonworks Data Platform?
The pricing model for Cloudera Data Platform is complex and has increased significantly compared to CDH. Initially, CDH had a straightforward pricing model based on nodes, but CDP includes factors ...
What needs improvement with Hortonworks Data Platform?
Cloudera Data Platform should include additional capabilities and features similar to those offered by other data management solutions like Azure ( /products/microsoft-azure-reviews ) and Databrick...
 

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
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