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 7.0. Dataiku holds a 13.0% 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

6,237 Views
1,076 Comparison Views

100% willing to recommend

IBM SPSS Modeler

Read 39 IBM SPSS Modeler reviews

1,528 Views
241 Comparison Views

86% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

598 Views
136 Comparison Views

93% willing to recommend

Dataiku

IBM SPSS Modeler

SAS Enterprise Miner

Comparison Buyer's Guide

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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, Knime, Amazon Web Services (AWS) and others in Data Science Platforms.

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

Buyer's Guide

Data Science Platforms

June 2025

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Helped 859,957 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 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 Modeler is 2.5%, up from 2.5% compared to the previous year. The mindshare of SAS Enterprise Miner is 0.9%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

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.

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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…

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Quotes from Members

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

Pros

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

"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."

"I believe the return on investment looks positive."

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

"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."

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

"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 solution is quite stable."

More Dataiku pros

"A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."

"New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data."

"Very good data aggregation."

"It works fine. I have not had any stability issues; it is always up."

"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."

"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."

"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."

"We have a local representative who specializes in SPSS. He will help us do the PoC."

More IBM SPSS Modeler pros

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

"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."

"The technical support is very good."

"he solution is scalable."

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

"The setup is straightforward. Deployment doesn't take more than 30 minutes."

"Good data management and analytics."

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

More SAS Enterprise Miner pros

Cons

"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)."

"There is room for improvement in terms of allowing for more code-based features."

"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."

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

"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."

"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."

More Dataiku cons

"The platform that you can deploy it on needs improvement because I think it is Windows only. I do not think it can run off a Red Hat, like the server products. I am pretty sure it is Windows and AIX only."

"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."

"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 challenge for the very technical data scientists: It is constraining for them."

"Customer support is hard to contact."

"Unstructured data is not appropriate for SPSS Modeler."

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

More IBM SPSS Modeler cons

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

"The initial setup is challenging if doing it for the first time."

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

"Technical support could be improved."

"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."

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

"Virtualization could be much better."

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

More SAS Enterprise Miner cons

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."

"If you are in a university and the license is free then you can use the tool without any charges, which is good."

"It is a huge increase to time savings."

"I am using the free version of IBM SPSS Modeler, it is the educational edition version."

"It is an expensive product."

"$5,000 annually."

"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%

Computer Software Company

10%

Manufacturing Company

Educational Organization

Financial Services Firm

12%

Educational Organization

10%

Government

University

Financial Services Firm

28%

University

10%

Educational Organization

Manufacturing Company

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...

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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?

There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the ser...

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 29% of the time

KNIME vs Dataiku

Compared 19% of the time

Alteryx vs Dataiku

Compared 12% of the time

Altair RapidMiner vs Dataiku

Compared 10% of the time

Starburst Enterprise vs Dataiku

Compared 1% of the time

More Dataiku Competitors

Microsoft Power BI vs IBM SPSS Modeler

Compared 25% of the time

IBM SPSS Statistics vs IBM SPSS Modeler

Compared 22% of the time

KNIME vs IBM SPSS Modeler

Compared 15% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 8% of the time

Amazon SageMaker vs IBM SPSS Modeler

Compared 2% of the time

More IBM SPSS Modeler Competitors

KNIME vs SAS Enterprise Miner

Compared 27% of the time

SAS Visual Analytics vs SAS Enterprise Miner

Compared 22% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 21% of the time

MathWorks Matlab vs SAS Enterprise Miner

Compared 9% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

Dataiku

June 2025

Download Dataiku product report

Buyer's Guide

IBM SPSS Modeler

June 2025

Download IBM SPSS Modeler product report

Buyer's Guide

Data Mining

June 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

June 2025

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