Cloudera Data Science Workbench vs IBM SPSS Modeler comparison

Cloudera and IBM are both solutions in the Data Science Platforms category. Cloudera is ranked #24 with an average rating of 6.0, while IBM is ranked #17 with an average rating of 7.5. Cloudera holds a 1.3% mindshare in Data Science Platforms, compared to IBM’s 2.5% mindshare. Additionally, 66% of Cloudera users are willing to recommend the solution, compared to 86% of IBM users who would recommend it.

Cloudera Data Science Workb...

Read 2 Cloudera Data Science Workbench reviews

836 Views
819 Comparison Views

66% willing to recommend

IBM SPSS Modeler

Read 40 IBM SPSS Modeler reviews

2,148 Views
1,418 Comparison Views

86% willing to recommend

Cloudera Data Science Workb...

IBM SPSS Modeler

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

IBM SPSS Modeler and Cloudera Data Science Workbench are competing products in data science tools. Cloudera has the upper hand with its robust feature set and scalability that many buyers find justify its cost.

Features: IBM SPSS Modeler has strengths in predictive analytics, machine learning capabilities, and easy integration with IBM's ecosystem. Cloudera Data Science Workbench provides scalable data processing, flexibility in coding languages, and strong integration with Hadoop ecosystems.

Ease of Deployment and Customer Service: IBM SPSS Modeler offers straightforward installation with comprehensive customer support resources. Cloudera Data Science Workbench requires a more complex setup but offers strong community support and a versatile infrastructure.

Pricing and ROI: IBM SPSS Modeler has a clear pricing model with predictable ROI, suitable for budget-conscious businesses. Cloudera Data Science Workbench involves higher setup costs, but its ROI is validated by enhanced capabilities and scalability, appealing to businesses seeking growth in data science.

To learn more, read our detailed Cloudera Data Science Workbench vs. IBM SPSS Modeler Report (Updated: July 2025).

Buyer's Guide

Cloudera Data Science Workbench vs. IBM SPSS Modeler

July 2025

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Helped 867,497 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 Data Science Workb...

Ranking in Data Science Platforms

24th

Average Rating

7.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

IBM SPSS Modeler

Ranking in Data Science Platforms

17th

Average Rating

8.0

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

Data Mining (4th)

Mindshare comparison

As of September 2025, in the Data Science Platforms category, the mindshare of Cloudera Data Science Workbench is 1.3%, down from 1.6% compared to the previous year. The mindshare of IBM SPSS Modeler is 2.5%, up from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
IBM SPSS Modeler	2.5%
Cloudera Data Science Workbench	1.3%
Other	96.2%

Data Science Platforms

Featured Reviews

Ismail Peer

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.

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PeterHuo

Application Architect at Canada Border Services Agency

Good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data

There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the server due to memory leaks. This performance problem bothers people. The performance issue seems to be related to the server. We design streams on the client and submit them to the server, which generates a large SQL statement. There are two potential bottlenecks: one in the server and another in data extraction. I'm unsure about the exact mechanics of data splitting when fetching from the database. When streams become larger, performance bottlenecks may occur in the IBM SPSS Modeler server or the database. Sometimes the server crashes and needs to be restarted to release memory on both sides. I'm not sure exactly where the problem is caused, as I focus on stream design rather than server issues. The problem could be on the IBM SPSS Modeler server and database.

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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."

"We use analytics with the visual modeling capability to leverage productivity improvements."

"It's very easy to use. The drag and drop feature makes it very easy when you are building and testing the streams. That's very useful."

"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."

"I was familiar with using IBM SPSS Modeler separately in the private sector before that. It's a good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data."

"Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms."

"Automated modelling, classification, or clustering are very useful."

"We are using it either for workforce deployment or to improve our operations."

"We have a local representative who specializes in SPSS. He will help us do the PoC."

More IBM SPSS Modeler pros

Cons

"Running this solution requires a minimum of 12GB to 16GB of RAM."

"The tool's MLOps is not good. It's pricing also needs to improve."

"The standard package (personal) is not supported for database connection."

"I can say the solution is outdated."

"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."

"Customer support is hard to contact."

"I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it."

"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."

"Unstructured data is not appropriate for SPSS Modeler."

"The forecasting could be a bit easier."

More IBM SPSS Modeler cons

Pricing and Cost Advice

"The product is expensive."

"The government has funds and a budget, it's hard to say if it's expensive or cheap. In Canada, they have a yearly budget. They used to encourage people to use the modeler for development. If ten users use the server with ten licenses, it runs faster. But if forty users use the same appliance, everything slows down. People then think it's not easy to do things and prefer using remote tools like Python to extract data from the database. It's not about being expensive or cheap, but about people's knowledge and experience in how to do the work."

"It is a huge increase to time savings."

"Its price is okay for a company, but for personal use, it is considered somewhat expensive."

"It is an expensive product."

"This tool, being an IBM product, is pretty expensive."

"$5,000 annually."

"The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint. It's expensive, but it's a good tool."

"It got us a good amount of money with quick and efficient modeling."

More IBM SPSS Modeler pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

34%

Healthcare Company

Computer Software Company

Manufacturing Company

Financial Services Firm

12%

Educational Organization

11%

Government

10%

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	4
Large Enterprise	32

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...

See all answers

What needs improvement with Cloudera Data Science Workbench?

The tool's MLOps is not good. It's pricing also needs to improve.

See all answers

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...

See all answers

What do you like most about IBM SPSS Modeler?

Compared to other tools, the product works much easier to analyze data without coding.

See all answers

What is your experience regarding pricing and costs for IBM SPSS Modeler?

The government has funds and a budget, it's hard to say if it's expensive or cheap. In Canada, they have a yearly budget. They used to encourage people to use the modeler for development. If ten us...

See all answers

What needs improvement with IBM SPSS Modeler?

The customer comes to you and says they want to deploy it and make a production out of this, which is very difficult and expensive with IBM SPSS Modeler. With MATLAB, there is no problem. I have a ...

See all answers

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Product Reports

Buyer's Guide

Data Science Platforms

August 2025

Download Cloudera Data Science Workbench product report

Buyer's Guide

IBM SPSS Modeler

September 2025

Download IBM SPSS Modeler product report

Also Known As

CDSW

SPSS Modeler

Overview

Cloudera Data Science Workbench (CDSW) makes secure, collaborative data science at scale a reality for the enterprise and accelerates the delivery of new data products. With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. Access any data anywhere – from cloud object storage to data warehouses, CDSW provides connectivity not only to CDH but the systems your data science teams rely on for analysis.

Cloudera

IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.

Buy
https://www.ibm.com/products/spss-modeler/pricing

Sign up for the trial
https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947

IBM

Sample Customers

IQVIA, Rush University Medical Center, Western Union

Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis Turkey

Buyer's Guide

Cloudera Data Science Workbench vs. IBM SPSS Modeler

July 2025

Free Report: Cloudera Data Science Workbench vs. IBM SPSS Modeler

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