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 6.8. Dataiku holds a 12.7% mindshare in Data Science Platforms, compared to IBM’s 2.4% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 86% of IBM users who would recommend it.

Dataiku

Read 12 Dataiku reviews

6,785 Views
5,638 Comparison Views

100% willing to recommend

IBM SPSS Modeler

Read 39 IBM SPSS Modeler reviews

1,793 Views
1,459 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 2025).

Buyer's Guide

Dataiku vs. IBM SPSS Modeler

March 2025

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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

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

6.6

Number of Reviews

Ranking in other categories

Data Mining (4th)

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Dataiku is 12.7%, up from 8.2% 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

RichardXu

Data Science Lead at a mining and metals company with 10,001+ employees

The platform organizes workflows visually and efficiently

One of the valuable features of Dataiku is the workflow capability. It allows us to organize a workflow efficiently. The platform has a visual interface, making it much easier for educated professionals to organize their work. This feature is useful because it simplifies tasks and eliminates the need for a data scientist. If you are knowledgeable about AI, you can directly write using primitive tools like Pantera flow, PyTorch, and Scikit-learn. However, Dataiku makes this process much easier.

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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

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

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

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

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

"The solution is quite stable."

"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."

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

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

More Dataiku pros

"It is just a lot faster. So you do not have to write a bunch of code, you can throw that stuff on there pretty quickly and do prototyping quickly."

"It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler."

"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."

"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."

"It is pretty scalable."

"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."

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

"I think the code modeling features are the most valuable and without the need to write a code back with many different possibilities to choose from. And the second one is linked to the activity of the data preparation."

More IBM SPSS Modeler pros

Cons

"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."

"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."

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

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

"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."

"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."

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

More Dataiku cons

"Requires more development."

"The challenge for the very technical data scientists: It is constraining for them."

"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."

"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."

"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."

"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."

"I would like better integration into the Weather Company solution. I have raised a couple of concerns about this integration and having more time series capabilities."

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

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."

"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."

"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."

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

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

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

"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."

"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."

"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

18%

Educational Organization

13%

Manufacturing Company

Computer Software Company

Financial Services Firm

13%

Educational Organization

12%

University

10%

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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?

There is room for improvement in terms of allowing for more code-based features. I would love for Dataiku to allow more flexibility with code-based components and provide the possibility to extend ...

See all answers

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

My company sells licenses for both Dataiku and Alteryx, and we have clients who use them. I engage with several companies in telecommunications, retail, and energy to assess how our clients are uti...

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

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Compared 12% of the time

Altair RapidMiner vs Dataiku

Compared 10% of the time

Starburst Galaxy vs Dataiku

Compared 1% of the time

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Compared 20% of the time

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Compared 16% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 7% of the time

SAS Analytics vs IBM SPSS Modeler

Compared 2% of the time

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Product Reports

Buyer's Guide

Dataiku

April 2025

Download Dataiku product report

Buyer's Guide

IBM SPSS Modeler

April 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

March 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: March 2025.

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