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Cloudera Data Science Workbench vs SAP Predictive Analytics comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

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 Data Science Workb...
Ranking in Data Science Platforms
22nd
Average Rating
7.0
Reviews Sentiment
6.9
Number of Reviews
2
Ranking in other categories
No ranking in other categories
SAP Predictive Analytics
Ranking in Data Science Platforms
27th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the Data Science Platforms category, the mindshare of Cloudera Data Science Workbench is 1.6%, up from 1.4% compared to the previous year. The mindshare of SAP Predictive Analytics is 0.9%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
Cloudera Data Science Workbench1.6%
SAP Predictive Analytics0.9%
Other97.5%
Data Science Platforms
 

Featured Reviews

Ismail Peer - PeerSpot reviewer
Program Management Lead Advisor at Unionbank Philippines
Useful for data science modeling but improvement is needed in MLOps and pricing
If you don't configure CDSW well, then it might be not useful for you. Deploying the tool can vary in complexity, but most of the time, it's relatively simple and straightforward. Triggering a job from data to production is easy, as the platform automates the deployment process. However, ensuring optimal resource allocation is essential for smooth operations.
AR
Senior Practice Manager - Head of SAP at a tech consulting company with 201-500 employees
Easy to implement, good data forecasting and reporting
This solution works for acquired data but not live, real-time data. If we connect it to a live backend system then we cannot perform predictive analytics on top of that. We have to first upload data to the cloud, manage the staging environment, and then perform the analysis. In the next release of this solution, I would like to see more automation in generating the models. The system can suggest the dimensions and measures that should be used, and pre-populate some of the information based on that. Power users would not have as much need for this, but this type of automation would be very helpful for business end-users.

Quotes from Members

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

Pros

"The Cloudera Data Science Workbench is customizable and easy to use."
"I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy to manage. Its API calls are also fast."
"I think the features of the actual ability to forecast and pull trends and correlations has been really good."
"The most valuable features are the analytics and reporting."
 

Cons

"The tool's MLOps is not good. It's pricing also needs to improve."
"Running this solution requires a minimum of 12GB to 16GB of RAM."
"This solution works for acquired data but not live, real-time data."
 

Pricing and Cost Advice

"The product is expensive."
"A free trial version is available for testing out this solution."
"The pricing is reasonable"
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Top Industries

By visitors reading reviews
Financial Services Firm
36%
Manufacturing Company
9%
Healthcare Company
7%
Computer Software Company
5%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

What do you like most about Cloudera Data Science Workbench?
I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy...
What needs improvement with Cloudera Data Science Workbench?
The tool's MLOps is not good. It's pricing also needs to improve.
What is your primary use case for Cloudera Data Science Workbench?
We have different use cases. Our banking use case uses machine learning to identify customer life events and recommend the best-suited card products. These machine-learning models are deployed in o...
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Also Known As

CDSW
SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA
 

Overview

 

Sample Customers

IQVIA, Rush University Medical Center, Western Union
mBank
Find out what your peers are saying about Cloudera Data Science Workbench vs. SAP Predictive Analytics and other solutions. Updated: December 2025.
881,114 professionals have used our research since 2012.