Cloudera Data Science Workbench vs IBM SPSS Modeler comparison

Cloudera and IBM are both solutions in the Data Science Platforms category. Cloudera is ranked #23 with an average rating of 6.0, while IBM is ranked #13 with an average rating of 6.8. Cloudera holds a 1.3% mindshare in Data Science Platforms, compared to IBM’s 2.4% 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

980 Views
809 Comparison Views

66% willing to recommend

IBM SPSS Modeler

Read 39 IBM SPSS Modeler reviews

1,698 Views
1,397 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: April 2025).

Buyer's Guide

Cloudera Data Science Workbench vs. IBM SPSS Modeler

April 2025

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Helped 851,604 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

23rd

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

13th

Average Rating

8.0

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Mining (4th)

Mindshare comparison

As of May 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 2.4%, down from 2.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

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.

Read full review

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.

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

"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."

"The Cloudera Data Science Workbench is customizable and easy to use."

"Stability is good."

"I think it is the point and drag features that are the most valuable. You can simply click at the windows, and then pull up the functions."

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

"So far, the stability has been rock solid."

"It helped me in that I didn't need to write them by hand, and I could get a result in one or two minutes. That helped me a lot."

"It gives you a GUI interface, which is a lot more user-friendly and easier to use compared to writing R scripts or Python."

"The visual modeling capability is one of its attractive features."

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

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 integration with sources and visualisation needs some improvement. The scalability needs improvement."

"I can say the solution is outdated."

"The product does not have a search function for tags."

"We have run into a few problems doing some entity matching/analytics."

"It would be beneficial if the tool would include more well-known machine learning algorithms."

"I would like see more programming languages added, like MATLAB. That would be better."

"Dimension reduction should be classified separately."

"C&DS will not meet our scalability needs."

More IBM SPSS Modeler cons

Pricing and Cost Advice

"The product is expensive."

"It is a huge increase to time savings."

"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."

"$5,000 annually."

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

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

"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."

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

"It is an expensive product."

More IBM SPSS Modeler pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

34%

Manufacturing Company

Healthcare Company

Computer Software Company

Financial Services Firm

13%

Educational Organization

11%

University

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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...

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?

See all answers

Comparisons

Amazon SageMaker vs Cloudera Data Science Workbench

Compared 28% of the time

Databricks vs Cloudera Data Science Workbench

Compared 27% of the time

Dataiku vs Cloudera Data Science Workbench

Compared 18% of the time

KNIME vs Cloudera Data Science Workbench

Compared 10% of the time

Google Cloud Datalab vs Cloudera Data Science Workbench

Compared 9% of the time

More Cloudera Data Science Workbench Competitors

Microsoft Power BI vs IBM SPSS Modeler

Compared 27% of the time

IBM SPSS Statistics vs IBM SPSS Modeler

Compared 20% of the time

KNIME vs IBM SPSS Modeler

Compared 15% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 8% of the time

Alteryx vs IBM SPSS Modeler

Compared 5% of the time

More IBM SPSS Modeler Competitors

Product Reports

Buyer's Guide

Data Science Platforms

May 2025

Download Cloudera Data Science Workbench product report

Buyer's Guide

IBM SPSS Modeler

May 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

April 2025

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

Find out what your peers are saying about Cloudera Data Science Workbench vs. IBM SPSS Modeler and other solutions. Updated: April 2025.

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