Dataiku vs IBM SPSS Modeler comparison

Dataiku and IBM are both solutions in the Data Science Platforms category. Dataiku is ranked #6 with an average rating of 8.2, while IBM is ranked #13 with an average rating of 8.0. Dataiku holds a 9.3% mindshare in Data Science Platforms, compared to IBM’s 3.9% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 86% of IBM users who would recommend it.

Dataiku

Read 14 Dataiku reviews

5,570 Views
5,459 Comparison Views

100% willing to recommend

IBM SPSS Modeler

Read 40 IBM SPSS Modeler reviews

2,386 Views
1,694 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: December 2025).

Buyer's Guide

Dataiku vs. IBM SPSS Modeler

December 2025

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Helped 879,259 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

6th

Average Rating

8.2

Reviews Sentiment

7.1

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

6.3

Number of Reviews

Ranking in other categories

Data Mining (3rd)

Mindshare comparison

As of December 2025, in the Data Science Platforms category, the mindshare of Dataiku is 9.3%, down from 11.7% compared to the previous year. The mindshare of IBM SPSS Modeler is 3.9%, up from 2.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Dataiku	9.3%
IBM SPSS Modeler	3.9%
Other	86.8%

Data Science Platforms

Featured Reviews

Durgesh-Singh

Head of Delivery & Practice (Data & AI) at a recruiting/HR firm with 201-500 employees

Unified data projects have accelerated development and simplified architecture for higher ROI

I do not see anything that I would improve or enhance in Dataiku at this time; overall, it is a good tool to incorporate and to suggest to customers. Currently, I do not see anything specific that I would include or any functionality that requires enhancement. Dataiku gives the complete picture of the AI universe, and we have not faced any glitches, so I do not have recommendations or suggestions for improvement. All products have room for improvement, and I would like to see their pricing simplified, as it is somewhat complex. In terms of documentation, there is substantial documentation available. Customer support is good, the product is scalable, and it provides flexibility to develop. Someone who needs to do coding can do it, and someone who does not know coding can also build solutions, but the pricing is complex, which I believe should be improved.

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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 highly regarded as it is a leader in the Gartner ranking."

"Cloud-based process run helps in not keeping the systems on while processes are running."

"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."

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

"The advantage is that you can focus on machine learning while having access to what they call 'recipes.' These recipes allow me to preprocess and prepare data without writing any code."

"Our clients can easily drag and drop components and use them on the spot."

"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."

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

More Dataiku pros

"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."

"We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive."

"The ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that."

"Stability is good."

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

"The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well."

"Automation is great and this product is very organized."

"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."

More IBM SPSS Modeler pros

Cons

"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."

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

"All products have room for improvement, and I would like to see their pricing simplified, as it is somewhat complex."

"We still encounter some integration issues."

"The ability to have charts right from the explorer would be an improvement."

"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."

"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."

"The license is very expensive."

More Dataiku cons

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

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

"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."

"It is not integrated with Qlik, Tableau, and Power BI."

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

"It would be good if IBM added help resources to the interface."

"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."

"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

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

"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."

"It is a huge increase to time savings."

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

"$5,000 annually."

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

"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."

More IBM SPSS Modeler pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Manufacturing Company

Computer Software Company

Energy/Utilities Company

Financial Services Firm

12%

Government

12%

University

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	8

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 find the pricing of Dataiku quite affordable for our customers, as they are usually large companies. However, it is a pricey solution and I primarily recommend it to bigger companies.

See all answers

What needs improvement with Dataiku Data Science Studio?

In terms of enhancing collaboration within my team, I would not say Dataiku is the best one because it's so expensive. We are not able to provide it to everyone. There are very few people who have ...

See all answers

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

My main use cases in Dataiku include ensuring a strong data pipeline ingestion. We have people from data management, so we need to take care of the pipeline, their data quality, data drifting, all ...

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

December 2025

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Buyer's Guide

IBM SPSS Modeler

December 2025

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

December 2025

Free Report: Dataiku vs. IBM SPSS Modeler

Find out what your peers are saying about Dataiku vs. IBM SPSS Modeler and other solutions. Updated: December 2025.

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