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Dataiku vs IBM SPSS Modeler comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

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
12
Ranking in other categories
No ranking in other categories
IBM SPSS Modeler
Ranking in Data Science Platforms
17th
Average Rating
8.0
Reviews Sentiment
6.3
Number of Reviews
40
Ranking in other categories
Data Mining (4th)
 

Mindshare comparison

As of September 2025, in the Data Science Platforms category, the mindshare of Dataiku is 12.3%, up from 10.3% compared to the previous year. The mindshare of IBM SPSS Modeler is 2.5%, up from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
Dataiku12.3%
IBM SPSS Modeler2.5%
Other85.2%
Data Science Platforms
 

Featured Reviews

RichardXu - PeerSpot reviewer
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.
PeterHuo - PeerSpot reviewer
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.

Quotes from Members

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

Pros

"Cloud-based process run helps in not keeping the systems on while processes are running."
"I rate the overall product as eight out of ten."
"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."
"I believe the return on investment looks positive."
"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."
"The solution is quite stable."
"We are creating models and putting them into production much faster than we would if we had just gone with a strict, code-based solution, like R or Python."
"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 quality is very good."
"Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms."
"It helped me in that I didn't need to write them by hand, and I could get a result in one or two minutes. That helped me a lot."
"It is a great product for running statistical analysis."
"We have integration where you can write third-party apps. This sort of feature opens it up to being able to do anything you want."
"Stability is good."
 

Cons

"The license is very expensive."
"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)."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."
"I think it would help if Data Science Studio added some more features and improved the data model."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"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."
"Expensive to deploy solutions. You need to buy an extra deployment unit."
"I can say the solution is outdated."
"Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization."
"The platform's cloud version needs improvements."
"We have run into a few problems doing some entity matching/analytics."
"​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.​"
"The integration with sources and visualisation needs some improvement. The scalability needs improvement."
 

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."
"This tool, being an IBM product, is pretty expensive."
"It is an expensive product."
"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."
"It is a huge increase to time savings."
"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."
"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."
"I am using the free version of IBM SPSS Modeler, it is the educational edition version."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
10%
Computer Software Company
9%
Energy/Utilities Company
6%
Financial Services Firm
12%
Educational Organization
11%
Government
10%
University
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise1
Large Enterprise7
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?
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.
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 ...
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...
What do you like most about IBM SPSS Modeler?
Compared to other tools, the product works much easier to analyze data without coding.
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...
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 and expensive with IBM SPSS Modeler. With MATLAB, there is no problem. I have a ...
 

Comparisons

 

Also Known As

Dataiku DSS
SPSS Modeler
 

Overview

 

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
Find out what your peers are saying about Dataiku vs. IBM SPSS Modeler and other solutions. Updated: July 2025.
867,370 professionals have used our research since 2012.