Dataiku vs IBM SPSS Modeler vs SAS Enterprise Miner 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 #17 with an average rating of 7.5. Dataiku holds a 12.3% mindshare in Data Science Platforms, compared to IBM’s 2.5% 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

6,079 Views
5,897 Comparison Views

100% willing to recommend

IBM SPSS Modeler

Read 40 IBM SPSS Modeler reviews

2,148 Views
1,418 Comparison Views

86% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

865 Views
623 Comparison Views

93% willing to recommend

Dataiku

IBM SPSS Modeler

SAS Enterprise Miner

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Executive Summary

We performed a comparison between Dataiku, IBM SPSS Modeler, and SAS Enterprise Miner based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Knime and others in Data Science Platforms.

To learn more, read our detailed Data Science Platforms Report (Updated: August 2025).

Buyer's Guide

Data Science Platforms

August 2025

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Helped 867,497 peers since 2012

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 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. The mindshare of SAS Enterprise Miner is 1.2%, up from 0.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Dataiku	12.3%
IBM SPSS Modeler	2.5%
SAS Enterprise Miner	1.2%
Other	84.0%

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.

Read full review

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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reviewer1352853

Executive Head of analytics at a retailer with 5,001-10,000 employees

A stable product that is easy to deploy and can be used for structured and unstructured data mining

We use the solution for predictive analytics to do structured and unstructured data mining I like the way the product visually shows the data pipeline. The product must provide better integration with cloud-native technologies. I have been using the solution for 20 years. The product is very…

Read full review

Quotes from Members

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

Pros

"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."

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

"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."

"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."

"I believe the return on investment looks positive."

"The solution is quite stable."

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

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

More Dataiku pros

"We have been able to do some predictive modeling with it"

"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."

"Very good data aggregation."

"The supervised models are valuable. It is also very organized and easy to use."

"Automated modelling, classification, or clustering are very useful."

"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 is a great product for running statistical analysis."

"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."

More IBM SPSS Modeler pros

"Good data management and analytics."

"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."

"The solution is very good for data mining or any mining issues."

"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."

"he solution is scalable."

"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."

"I like the way the product visually shows the data pipeline."

"The most valuable feature is the decision tree creation."

More SAS Enterprise Miner pros

Cons

"The license is very expensive."

"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."

"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."

"We still encounter some integration issues."

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

"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."

"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."

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

More Dataiku cons

"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."

"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."

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

"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."

"It is not integrated with Qlik, Tableau, and Power BI."

"Initial setup of the software was complex, because of our own problems within the government."

"Unstructured data is not appropriate for SPSS Modeler."

"I think mapping for geographic data would also be a really great thing to be able to use."

More IBM SPSS Modeler cons

"The ease of use can be improved. When you are new it seems a bit complex."

"The solution is much more complex than other options."

"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."

"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."

"Virtualization could be much better."

"The visualization of the models is not very attractive, so the graphics should be improved."

"The user interface of the solution needs improvement. It needs to be more visual."

"The product must provide better integration with cloud-native technologies."

More SAS Enterprise Miner 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 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."

"It is a huge increase to time savings."

"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."

"This tool, being an IBM product, is pretty expensive."

"It got us a good amount of money with quick and efficient modeling."

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

More IBM SPSS Modeler pricing and cost advice

"The solution must improve its licensing models."

"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."

"This solution is for large corporations because not everybody can afford it."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Manufacturing Company

10%

Computer Software Company

Energy/Utilities Company

Financial Services Firm

12%

Educational Organization

11%

Government

10%

University

Financial Services Firm

26%

University

11%

Educational Organization

11%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	1
Large Enterprise	7

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	4
Large Enterprise	32

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	4
Large Enterprise	7

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...

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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 mo...

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 compa...

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 bud...

See all answers

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 ...

See all answers

What do you like most about SAS Enterprise Miner?

I like the way the product visually shows the data pipeline.

See all answers

What is your experience regarding pricing and costs for SAS Enterprise Miner?

The solution must improve its licensing models. It bundles all the products into smaller products. We can only have a...

See all answers

What needs improvement with SAS Enterprise Miner?

The product must provide better integration with cloud-native technologies.

See all answers

Comparisons

Databricks vs Dataiku

Compared 27% of the time

KNIME Business Hub vs Dataiku

Compared 20% of the time

Alteryx vs Dataiku

Compared 12% of the time

Altair RapidMiner vs Dataiku

Compared 10% of the time

Amazon SageMaker vs Dataiku

Compared 9% of the time

More Dataiku Competitors

IBM SPSS Statistics vs IBM SPSS Modeler

Compared 30% of the time

Microsoft Power BI vs IBM SPSS Modeler

Compared 21% of the time

KNIME Business Hub vs IBM SPSS Modeler

Compared 14% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 6% of the time

More IBM SPSS Modeler Competitors

KNIME Business Hub vs SAS Enterprise Miner

Compared 31% of the time

SAS Visual Analytics vs SAS Enterprise Miner

Compared 14% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 14% of the time

TIBCO Data Science vs SAS Enterprise Miner

Compared 7% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

Dataiku

September 2025

Download Dataiku product report

Buyer's Guide

IBM SPSS Modeler

September 2025

Download IBM SPSS Modeler product report

Buyer's Guide

Data Mining

August 2025

Download SAS Enterprise Miner product report

Also Known As

Dataiku DSS

SPSS Modeler

Enterprise Miner

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

SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.

SAS

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

Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare

Buyer's Guide

Data Science Platforms

August 2025

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