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 17 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

Download the report

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

Download the complete report

Helped 884,266 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

Dataiku

Ranking in Data Science Platforms

4th

Average Rating

8.0

Reviews Sentiment

6.8

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

PriyankaSharma3

Cdao/Global Head Of Data And Analytics at Givaudan Roure

Unified platform has accelerated model development and improved collaborative data science work

I think Dataiku could be improved or enhanced in future releases with more 'talk to my data' capabilities, maybe more NLP features, and maybe a platform to build agents. These improvements would benefit me and my processes because they will help us to continue using Dataiku as one platform; right now we are exploring other platforms for the features which are missing, and if they are available within the same platform, I think it will increase the usage of Dataiku further. I think the pricing and licensing of Dataiku is a bit expensive; it could be improved further, and I think they should have a different kind of licensing model as well.

Read full review

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.

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 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."

"The most valuable feature is the set of visual data preparation tools."

"The best feature in Dataiku is that once the data is connected in the underneath layer, it flows exceptionally smoothly if you know how to tweak it."

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

"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."

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

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

"The best features Dataiku offers include the ability for users to use the node without having to code and the functionality related to low-code/no-code."

More Dataiku pros

"We have full control of the data handling process."

"Some basic form of feature engineering for classification models. This really quickens the model development process."

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

"The supervised models are valuable. It is also very organized and easy to use."

"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."

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

"Our business units' capabilities with SPSS Modeler is high. They no longer waste time on modeling and algorithms, meaning they are not coding any more. For example, segmentation projects now take one to three months, rather than six months to a year, as before."

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

More IBM SPSS Modeler pros

Cons

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

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

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

"I have not seen a return on investment with Dataiku in terms of time saved, money saved, or fewer employees needed."

"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."

"One area for improvement is the need for more capabilities similar to those provided by NVIDIA for parallel machine learning training. We still encounter some integration issues."

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

"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."

More Dataiku cons

"Requires more development."

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

"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS. It still needs some tweaking."

"I can say the solution is outdated."

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

"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."

"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."

"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."

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

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

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

"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 is an expensive product."

"Having in mind all four tools from Garner’s top quadrant, the pricing of this tool is competitive and it reflects the quality that it offers."

"It is a huge increase to time savings."

"$5,000 annually."

More IBM SPSS Modeler pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.

See recommendations

884,266 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

17%

Manufacturing Company

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	4
Midsize Enterprise	2
Large Enterprise	11

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

Comparisons

Databricks vs Dataiku

Compared 22% of the time

KNIME Business Hub vs Dataiku

Compared 14% of the time

Alteryx vs Dataiku

Compared 11% of the time

Altair RapidMiner vs Dataiku

Compared 6% of the time

More Dataiku Competitors

IBM SPSS Statistics vs IBM SPSS Modeler

Compared 43% of the time

Microsoft Power BI vs IBM SPSS Modeler

Compared 6% of the time

KNIME Business Hub vs IBM SPSS Modeler

Compared 5% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 3% of the time

Databricks vs IBM SPSS Modeler

Compared 2% of the time

More IBM SPSS Modeler Competitors

Product Reports

Buyer's Guide

Dataiku

March 2026

Download Dataiku product report

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.

DOWNLOAD NOW

884,266 professionals have used our research since 2012.

See our Dataiku vs. IBM SPSS Modeler report.

See our list of best Data Science Platforms vendors.

We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.