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Dataiku vs IBM SPSS Statistics 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 Statistics
Ranking in Data Science Platforms
8th
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
39
Ranking in other categories
Data Mining (2nd)
 

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 Statistics is 3.0%, up from 2.8% 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 Statistics3.0%
Other84.7%
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.
Laurence Moseley - PeerSpot reviewer
Delivers reliable results for academic research and keeps you close to your data.
SPSS is perfectly adequate if all you want are some results. If you only need the results, you do not require the trail of evidence on how you obtained those results. I mainly used it for cross tabs, correlation, regression, chi-squared tests, and similar analyses often seen in published papers; I used it for my papers as well. For wider uses I find Knime keeps me in touch with my data, however much I transform them.

Quotes from Members

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

Pros

"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."
"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 believe the return on investment looks positive."
"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."
"The most valuable feature is the set of visual data preparation tools."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."
"The solution is quite stable."
"SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools."
"You can quickly build models because it does the work for you."
"It is perfectly adequate if all you need are the results and not the trail of evidence."
"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."
"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."
"The learning curve to using this product is not steep. The program is appropriate for those who do not have a lot of background in programming, yet have to perform basic statistical analysis."
"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."
"IBM SPSS Statistics depends on AI."
 

Cons

"There is room for improvement in terms of allowing for more code-based features."
"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 ability to have charts right from the explorer would be an improvement."
"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."
"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 think it would help if Data Science Studio added some more features and improved the data model."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"The technical support should be improved."
"Improvements are needed in the user interface, particularly in terms of user-friendliness."
"In some cases, the product takes time to load a large dataset. They could improve this particular area."
"This solution is not suitable for use with Big Data."
"There is a learning curve; it's not very steep, but there is one."
"Better documentation on how to use macros."
"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."
"I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable."
 

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."
"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."
"While the pricing of the product may be higher, the accompanying service and features justify the investment."
"The price of IBM SPSS Statistics could improve."
"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
"We think that IBM SPSS is expensive for this function."
"I rate the tool's pricing a five out of ten."
"More affordable training for new staff members."
"It's quite expensive, but they do a special deal for universities."
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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
18%
Computer Software Company
8%
Manufacturing Company
8%
University
7%
 

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 Enterprise6
Large Enterprise19
 

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 Statistics?
The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
I think the price of the solution is very reasonable. The cost depends; you have the option for subscription or you can purchase the license. Most of our customers are paying every year for a type ...
What needs improvement with IBM SPSS Statistics?
I have faced some challenges with IBM SPSS Statistics; you need to know what you're doing because it's not very user-friendly. It's not something a person can come and intuitively work with. The ba...
 

Also Known As

Dataiku DSS
SPSS Statistics
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
Find out what your peers are saying about Dataiku vs. IBM SPSS Statistics and other solutions. Updated: July 2025.
867,370 professionals have used our research since 2012.