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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 (3rd)
 

Mindshare comparison

As of July 2025, in the Data Science Platforms category, the mindshare of Dataiku is 13.0%, up from 9.2% compared to the previous year. The mindshare of IBM SPSS Statistics is 2.8%, down from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
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."
"One of the valuable features of Dataiku is the workflow capability."
"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."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"The software offers consistency across multiple research projects helping us with predictive analytics capabilities."
"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."
"The most valuable feature is its robust statistical analysis capabilities."
"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."
"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"SPSS is perfectly adequate if all you want are some results."
"in terms of the simplicity, I think the SPSS basic can handle it."
"The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful."
 

Cons

"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"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)."
"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."
"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."
"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."
"We still encounter some integration issues."
"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."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"The design of the experience can be improved."
"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."
"The solution needs to improve forecasting using time series analysis."
"The product should provide more ways to import data and export results that are user-friendly for high-level executives."
"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."
"In some cases, the product takes time to load a large dataset. They could improve this particular area."
"Improvements are needed in the user interface, particularly in terms of user-friendliness."
 

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."
"I rate the tool's pricing a five out of ten."
"The price of IBM SPSS Statistics could improve."
"While the pricing of the product may be higher, the accompanying service and features justify the investment."
"Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."
"It's quite expensive, but they do a special deal for universities."
"More affordable training for new staff members."
"We think that IBM SPSS is expensive for this function."
"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
9%
Computer Software Company
9%
Energy/Utilities Company
6%
Financial Services Firm
17%
Computer Software Company
8%
Manufacturing Company
8%
University
8%
 

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.
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?
SPSS is horrendously expensiver. On a laptop Knime is free of charge (Windows, Mac, Linux)
What needs improvement with IBM SPSS Statistics?
Better guidance both in producing programs and interpreting their output.
 

Comparisons

 

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: June 2025.
861,524 professionals have used our research since 2012.