Dataiku vs IBM SPSS Modeler comparison

Dataiku and IBM are both solutions in the Data Science Platforms category. Dataiku is ranked #4 with an average rating of 8.0, while IBM is ranked #12 with an average rating of 8.0. Dataiku holds a 6.7% mindshare in Data Science Platforms, compared to IBM’s 3.5% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 86% of IBM users who would recommend it.

Dataiku

Read 20 Dataiku reviews

5,913 Views
5,795 Comparison Views

100% willing to recommend

IBM SPSS Modeler

Read 40 IBM SPSS Modeler reviews

2,814 Views
2,082 Comparison Views

86% willing to recommend

Dataiku

IBM SPSS Modeler

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

IBM SPSS Modeler and Dataiku are leading tools in data analysis and modeling. Dataiku is often preferred for its comprehensive features that many users feel justify the higher cost.

Features:IBM SPSS Modeler excels in predictive modeling, statistical analysis, and integration with IBM's ecosystem. It offers robust visual programming capabilities and combines different techniques like regression and neural networks in one node. Dataiku stands out with its collaborative data science platform, extensive machine learning tools, and easy integration with diverse data environments. It provides advanced data preparation and supports code from languages like Python and R.

Room for Improvement:IBM SPSS Modeler's visual modeling is less advanced than other software solutions, and its integration for governance and security needs to be enhanced. It's complex to use for beginners without data science expertise. Dataiku could improve its cost efficiency as the perceived value often comes with a steep price. Its user interface, while comprehensive, can be overwhelming for new users, and some users feel the automation of certain tasks could be further developed to enhance usability.

Ease of Deployment and Customer Service:IBM SPSS Modeler provides a structured deployment process with support from IBM’s network, which some users find rigid. Dataiku offers a flexible deployment model, favoring seamless integration and iterative updates, coupled with a responsive support team that provides personalized attention.

Pricing and ROI:IBM SPSS Modeler involves a higher initial setup cost due to its enterprise-grade features, promising long-term value with an emphasis on advanced analytics. Dataiku presents a scalable pricing structure, appealing to businesses seeking flexible data solutions. Both offer valuable returns, with IBM focusing on comprehensive analytics and Dataiku on flexibility and scalability.

To learn more, read our detailed Dataiku vs. IBM SPSS Modeler Report (Updated: March 2026).

Buyer's Guide

Dataiku vs. IBM SPSS Modeler

March 2026

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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

Dataiku

Ranking in Data Science Platforms

4th

Average Rating

8.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

IBM SPSS Modeler

Ranking in Data Science Platforms

12th

Average Rating

8.0

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

Data Mining (3rd)

Mindshare comparison

As of March 2026, in the Data Science Platforms category, the mindshare of Dataiku is 6.7%, down from 12.5% compared to the previous year. The mindshare of IBM SPSS Modeler is 3.5%, up from 2.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Dataiku	6.7%
IBM SPSS Modeler	3.5%
Other	89.8%

Data Science Platforms

Featured Reviews

Shubhamkumar Gomar

Senior Data Scientist at Deloitte

Visual workflows have streamlined healthcare analytics and have reduced reporting time significantly

In terms of improvement, I cannot comment on the LLMs or the agentic view as I have not used them yet. However, I feel that better documentation is necessary. Dataiku should establish a stronger community since this is proprietary software, where users can share knowledge. Although they have some community interaction, it is often challenging to find assistance when stuck. For example, when I was new to Dataiku and trying to use an external optimization tool such as CPLEX, I struggled with resource directory linking to a project's notebook. Detailed documentation and community discussions could have significantly alleviated these issues for users such as myself.

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Prof. Dr. Rudolf Bisping

Business Owner at SASS GmbH

Support and flexibility enable effective project initiation and meet customer needs but deployment requires enhancement

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 solution, and then I convert my MATLAB solution to C programming language. This I can deploy, and I can check it, and it is MISRA compatible. It is very easy to deploy it, to go from MATLAB to C or C++, which is actually needed in the car industry. In the car industry, they want to have it in the hardware. You cannot put MATLAB or IBM SPSS Modeler in the hardware of a car, but with C, there is no problem with a microcontroller. They can shoot it into the microcontroller, and I can check it with Polyspace, and it is MISRA compatible, which is an industrial standard. There is nothing similar in IBM SPSS Modeler. I made solutions with IBM SPSS Modeler, and then the customer said they wanted to make a production out of it, and it was not possible. I stopped with IBM SPSS Modeler 18. It is now 18.6 from what I know at the moment. I do not believe that there is a possibility to design a graphic user interface with it. It is itself a graphic user interface, where you put all sorts of little icons into the display.

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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

"Dataiku is a complete platform to build ETL and data pipeline and deploy it, which I appreciate."

"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."

"I consider the return on investment with Dataiku valuable because for us, it is one single platform where all our data scientists come together and work on any model building, so it is collaboration, plus having everything in one place, organized, having proper project management, and then built-in capabilities which help to facilitate model building."

"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."

"The solution is quite stable."

"One of the valuable features of Dataiku is the workflow capability."

"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."

"I rate the overall product as eight out of ten."

More Dataiku pros

"It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale it"

"It is very scalable for non-technical people."

"We have been able to do some predictive modeling with it"

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

"It continues to be a very flexible platform, so that it handles R and Python and other types of technology. It seems to be growing with additional open-source movement out there on different platforms."

"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."

"A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."

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

More IBM SPSS Modeler pros

Cons

"I think it would help if Data Science Studio added some more features and improved the data model."

"Dataiku's scalability is not one of the best solutions to scale."

"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."

"We still encounter some integration issues."

"There is room for improvement in terms of allowing for more code-based features."

"The license is very expensive."

"However, I feel that better documentation is necessary."

"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."

More Dataiku cons

"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."

"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."

"When I used it in the office, back in the day, we did have some stability issues. Sometimes it just randomly crashed and we couldn't get good feedback. But when I use it for my own stuff now I don't have any problems."

"Customer support is hard to contact."

"Neural networks are quite simple, and now neural networks are evolving to these architecture related to deep learning, etc. They didn't incorporate this in IBM SPSS Modeler."

"The platform's cloud version needs improvements."

"If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement."

"The forecasting could be a bit easier."

More IBM SPSS Modeler cons

Pricing and Cost Advice

"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."

"Pricing is pretty steep. Dataiku is also not that cheap."

"It is an expensive product."

"$5,000 annually."

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

"When you are close to end of quarter, IBM and its partners can get you 60% to 70% discounts, so literally wait for the last day of the quarter for the best prices. You may feel like you are getting robbed if you can't receive a good discount."

"If you are in a university and the license is free then you can use the tool without any charges, which is good."

"It is a huge increase to time savings."

"I am using the free version of IBM SPSS Modeler, it is the educational edition version."

"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."

More IBM SPSS Modeler pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Manufacturing Company

10%

Computer Software Company

Energy/Utilities Company

Government

11%

Financial Services Firm

10%

University

Outsourcing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	2
Large Enterprise	13

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

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?

I am not the person involved in the process regarding pricing, setup cost, and licensing.

See all answers

What needs improvement with Dataiku Data Science Studio?

To improve Dataiku, it could enhance its visualization features, as it is not possible in Dataiku to create direct visualizations or to integrate a web app directly or in a simpler way as it is pos...

See all answers

What is your primary use case for Dataiku Data Science Studio?

My main use case for Dataiku is for data science and AI projects. I use Dataiku for a demand forecasting use case where the objective is to predict the demand for each product for the next four mon...

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

What is your primary use case for IBM SPSS Modeler?

I have been using IBM SPSS Modeler for a long time. I am using IBM SPSS Modeler mainly for ETL. Sometimes I use it to compare the results of the modeling as compared to MATLAB. MATLAB is the main t...

See all answers

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Product Reports

Buyer's Guide

Dataiku

March 2026

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Buyer's Guide

IBM SPSS Modeler

March 2026

Download IBM SPSS Modeler product report

Also Known As

Dataiku DSS

SPSS Modeler

Overview

Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.

Dataiku

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

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto

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

Dataiku vs. IBM SPSS Modeler

March 2026

Free Report: Dataiku vs. IBM SPSS Modeler

Find out what your peers are saying about Dataiku vs. IBM SPSS Modeler and other solutions. Updated: March 2026.

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