No more typing reviews! Try our Samantha, our new voice AI agent.

Dataiku vs Domino Data Science Platform vs IBM SPSS Modeler comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Mindshare comparison

As of April 2026, in the Data Science Platforms category, the mindshare of Dataiku is 5.9%, down from 12.7% compared to the previous year. The mindshare of Domino Data Science Platform is 2.1%, down from 2.5% compared to the previous year. The mindshare of IBM SPSS Modeler is 3.2%, up from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Dataiku5.9%
IBM SPSS Modeler3.2%
Domino Data Science Platform2.1%
Other88.8%
Data Science Platforms
 

Featured Reviews

SK
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.
AS
Machine Learning Engineer at Unemployed
Accelerated machine learning model development with seamless deployment
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar to using Git. Each user operates on their own equivalent of a branch or fork, and once finished, they…
RB
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.

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."
"Dataiku has positively impacted my organization since we use it majorly for our day-to-day work, and it is very helpful in creating and managing ETL pipelines to create a project flow, making it easy to go back to any step and then make edits if some changes occur."
"Dataiku is really a very intuitive platform that allows you to carry out data projects from end to end, with the opportunity to reuse templates, models, and recipes, which is one of the big advantages of using it."
"Dataiku has positively impacted my organization, specifically in one project where we performed migration from AWS to Dataiku, speeding up the solution by close to 40% and reducing architecture costs by almost 70%, which was a significant benefit and greatly impacted our operations."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"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."
"Compared to Informatica, this tool is extremely easy with its GUI-based functionality and large compatibility with various data sources, and maintenance processes are much more automated than ever, with fewer errors."
"The most valuable feature is the set of visual data preparation tools."
"The workspaces, which are like wrappers of Docker containers, made it easy to start development environments using Domino."
"The scalability of the solution is good; I'd rate it four out of five."
"We primarily use the solution for customer retention, but there are a lot of use cases for this particular product."
"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."
"I would recommend SPSS to someone who has just started trying to run a lot of modeling, it's a good starting point."
"It handles large data better than the previous system that we were using, which was basically Excel and Access. We serve upwards of 300,000 parts over a 150 regions and we need to crunch a lot of numbers."
"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."
"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."
"In the solution, I like the virtualization of data flow since it shows what goes where, which is mostly the strength of the tool."
"It will scale up to anything we need."
"We have a local representative who specializes in SPSS. He will help us do the PoC."
 

Cons

"I have not seen a return on investment with Dataiku in terms of time saved, money saved, or fewer employees needed."
"Dataiku's scalability is not one of the best solutions to scale."
"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."
"I find that it is a little slow during use. When I use Dataiku to run my script to transfer data, it takes more time than I would expect for the operation to complete."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"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."
"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."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"The predictive analysis feature needs improvement."
"The deployment of large language models (LLMs) could be improved."
"The predictive analysis feature needs improvement."
"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."
"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."
"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."
"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."
"The platform that you can deploy it on needs improvement because I think it is Windows only."
"I would like see more programming languages added, like MATLAB."
"It would be beneficial if the tool would include more well-known machine learning algorithms."
"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."
 

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."
Information not available
"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 is an expensive product."
"It got us a good amount of money with quick and efficient modeling."
"This tool, being an IBM product, is pretty expensive."
"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."
"Its price is okay for a company, but for personal use, it is considered somewhat expensive."
"It is a huge increase to time savings."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
886,906 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
9%
Computer Software Company
9%
Energy/Utilities Company
6%
Financial Services Firm
37%
Manufacturing Company
9%
Insurance Company
8%
Healthcare Company
5%
Financial Services Firm
10%
Government
10%
University
8%
Outsourcing Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise2
Large Enterprise13
No data available
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise4
Large Enterprise32
 

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?
The licenses are a bit high for companies that are still hesitating to get started with using Dataiku. For my persona...
What needs improvement with Dataiku Data Science Studio?
I have no suggestions for improvements because it's all good; it just sometimes lags a lot, and I don't know if the s...
What is your primary use case for Dataiku Data Science Studio?
My main use case for Dataiku involves ETL pipelines, mainly for data analysis, and I majorly use SQL queries for that...
What needs improvement with Domino Data Science Platform?
The deployment of large language models (LLMs) could be improved. Currently, Domino provides a simple server that can...
What is your primary use case for Domino Data Science Platform?
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-e...
What advice do you have for others considering Domino Data Science Platform?
It's important to have a DevOps team well-versed with cloud-native solutions to manage Domino effectively. Relying so...
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 bud...
What needs improvement with IBM SPSS Modeler?
The customer comes to you and says they want to deploy it and make a production out of this, which is very difficult ...
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...
 

Also Known As

Dataiku DSS
Domino Data Lab Platform
SPSS Modeler
 

Interactive Demo

Demo not available
Demo not available
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Allstate, GSK, AstraZeneca, Federal Reserve, US Navy, Bristol Myers Squibb, Bayer, BNP Paribas, Moodys, New York Life
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
Find out what your peers are saying about Databricks, Dataiku, Amazon Web Services (AWS) and others in Data Science Platforms. Updated: April 2026.
886,906 professionals have used our research since 2012.