Dataiku vs IBM SPSS Modeler vs KNIME Business Hub 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 #19 with an average rating of 7.0. Dataiku holds a 12.9% mindshare in Data Science Platforms, compared to IBM’s 2.6% 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

6,233 Views
6,046 Comparison Views

100% willing to recommend

IBM SPSS Modeler

Read 40 IBM SPSS Modeler reviews

2,195 Views
1,449 Comparison Views

86% willing to recommend

KNIME Business Hub

Read 60 KNIME Business Hub reviews

10,110 Views
7,077 Comparison Views

94% willing to recommend

Dataiku

IBM SPSS Modeler

KNIME Business Hub

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Dataiku, IBM SPSS Modeler, and KNIME Business Hub 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: August 2025).

Buyer's Guide

Data Science Platforms

August 2025

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Helped 866,088 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 August 2025, in the Data Science Platforms category, the mindshare of Dataiku is 12.9%, up from 9.7% compared to the previous year. The mindshare of IBM SPSS Modeler is 2.6%, up from 2.5% compared to the previous year. The mindshare of KNIME Business Hub is 11.9%, up from 10.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
KNIME Business Hub	11.9%
Dataiku	12.9%
IBM SPSS Modeler	2.6%
Other	72.6%

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.

Read full review

Laurence Moseley

Emeritus Professor of Health Services Research at University of South Wales

Has a drag-and-drop interface and AI capabilities

It's difficult to pinpoint one single feature because KNIME has so many. For starters, it's very easy to learn. You can get started with just a one-hour video. The drag-and-drop interface makes it user-friendly. For example, if you want to read an Excel file, drag the "read Excel file" node from the repository, configure it by specifying the file location, and run it. This gives you a table with all your data. Next, you can clean the data by handling missing values, selecting specific columns you want to analyze, and then proceeding with your analysis, such as regression or correlation. KNIME has over 4,500 nodes available for download. In addition, KNIME offers various extensions. For instance, the text processing extension allows you to process text data efficiently. It's more powerful than other tools like NVivo and Palantir. KNIME also has AI capabilities. If you're unsure about the next step, the AI assistant can suggest the most frequently used nodes based on your previous work. Another valuable feature is the integration with Python. If you need to perform a task that requires Python, you can simply add a Python node, write the necessary code,

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

"The solution is quite stable."

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

"Cloud-based process run helps in not keeping the systems on while processes are running."

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

"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."

"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."

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

"Dataiku is highly regarded as it is a leader in the Gartner ranking."

More Dataiku pros

"Compared to other tools, the product works much easier to analyze data without coding."

"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."

"I think the code modeling features are the most valuable and without the need to write a code back with many different possibilities to choose from. And the second one is linked to the activity of the data preparation."

"Stability is good."

"Our go live process has been slightly enhanced compared to the previous programmatic process. There is now a faster time to production from the business end."

"The visual modeling capability is one of its attractive features."

"It is a great product for running statistical analysis."

"It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler."

More IBM SPSS Modeler pros

"The solution allows for sharing model designs and model operations with other data analysts."

"I've tried to utilize KNIME to the fullest extent possible to replace Excel."

"KNIME is more intuitive and easier to use, which is the principal advantage."

"I would rate the stability of KNIME a ten out of ten."

"It is very fast to develop solutions."

"There are a lot of connectors available in KNIME."

"It is possible to configure the system to effectively manage memory and space requirements."

"The tool's analytic capabilities are good."

More KNIME Business Hub pros

Cons

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

"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."

"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."

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

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

"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."

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

More Dataiku cons

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

"It's not as user friendly as it could be."

"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."

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

"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."

"The platform's cloud version needs improvements."

"We have run into a few problems doing some entity matching/analytics."

"Expensive to deploy solutions. You need to buy an extra deployment unit."

More IBM SPSS Modeler cons

"I've had some problems integrating KNIME with other solutions."

"The solution is inconvenient when it comes to wrangling data that includes multiple steps or features because each step or feature requires its own icon."

"The current UI is primarily in English. Analyzing data in local languages might present challenges or issues."

"If they had a more structured training model it would be very helpful."

"It could input more data acquisitions from other sources and it is difficult to combine with Python."

"I wish there were more video training resources for KNIME. The current videos are very short, and most learning is text-based. Longer training sessions would be helpful, especially for complex flowchart use cases. Webinars focusing on starting projects and analyzing data would also be beneficial."

"The pricing needs improvement."

"The overall user experience feels unpolished. In particular: Data field type conversion is a real hassle, and date fields are a hassle; documentation is pretty poor; user community is average at best."

More KNIME Business Hub 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."

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

"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."

"When you are close to end of quarter, IBM and its partners can get you 60% to 70% discounts, so literally wait for the last day of the quarter for the best prices. You may feel like you are getting robbed if you can't receive a good discount."

"It is a huge increase to time savings."

"$5,000 annually."

"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."

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

More IBM SPSS Modeler pricing and cost advice

"The client versions are mostly free, and we pay only for the KNIME server version. It's not a cheap solution."

"I use the open-source version."

"KNIME is free and open source."

"Scaling to the on-premises version requires a licensing fee per user that is a bit expensive in comparison to R, Python, and SAS."

"At this time, I am using the free version of Knime."

"KNIME is a cheap product. I currently use KNIME's open-source version."

"This is an open-source solution that is free to use."

"KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required."

More KNIME Business Hub pricing and cost advice

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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

11%

Manufacturing Company

10%

University

Computer Software 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	31

By reviewers
Company Size	Count
Small Business	20
Midsize Enterprise	16
Large Enterprise	29

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...

See all answers

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 KNIME?

Since KNIME is a no-code platform, it is easy to work with.

See all answers

What is your experience regarding pricing and costs for KNIME?

I rate the product’s pricing a seven out of ten, where one is cheap and ten is expensive.

See all answers

What needs improvement with KNIME?

I have seen the potential to interact with Python, which is currently a bit limited. I am interested in the newer ver...

See all answers

Comparisons

Databricks vs Dataiku

Compared 28% 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

Starburst Galaxy vs Dataiku

Compared 1% of the time

More Dataiku Competitors

Microsoft Power BI vs IBM SPSS Modeler

Compared 24% of the time

IBM SPSS Statistics vs IBM SPSS Modeler

Compared 24% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 7% of the time

Alteryx vs IBM SPSS Modeler

Compared 6% of the time

Amazon SageMaker vs IBM SPSS Modeler

Compared 2% of the time

More IBM SPSS Modeler Competitors

Altair RapidMiner vs KNIME Business Hub

Compared 24% of the time

Microsoft Power BI vs KNIME Business Hub

Compared 12% of the time

Microsoft Azure Machine Learning Studio vs KNIME Business Hub

Compared 8% of the time

Alteryx vs KNIME Business Hub

Compared 7% of the time

SAS Enterprise Miner vs KNIME Business Hub

Compared 2% of the time

More KNIME Business Hub Competitors

Product Reports

Buyer's Guide

Dataiku

August 2025

Download Dataiku product report

Buyer's Guide

IBM SPSS Modeler

August 2025

Download IBM SPSS Modeler product report

Buyer's Guide

KNIME Business Hub

August 2025

Download KNIME Business Hub product report

Also Known As

Dataiku DSS

SPSS Modeler

KNIME Analytics Platform

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

KNIME Business Hub offers a no-code interface for data preparation and integration, making analytics and machine learning accessible. Its extensive node library allows seamless workflow execution across various data tasks.

KNIME Business Hub stands out for its user-friendly, no-code platform, promoting efficient data preparation and integration, even with Python and R. Its node library covers extensive data processes from ETL to machine learning. Community support aids users, enhancing productivity with minimal coding. However, its visualization, documentation, and interface require refinement. Larger data tasks face performance hurdles, demanding enhanced cloud connectivity and library expansions for deep learning efficiencies.

What are the most important features of KNIME Business Hub?

No-Code Interface: Simplifies data preparation without coding expertise.
Node Library: Supports diverse data tasks, including ETL and machine learning.
Python and R Integration: Seamlessly connects with popular programming languages.
Automation Capabilities: Enhances workflow productivity.
Visual Workflow Tools: Offers efficient data handling with visual aids.

What benefits and ROI can users expect from KNIME Business Hub?

Increased Productivity: Streamlined data tasks reduce development time.
Community Support: Access to extensive resources and user assistance.
Cost-Effective: Robust performance even on standard hardware.
Accessible Learning Curve: Simplicity allows easy access for educational and professional use.
Enhanced Prototyping: Ideal for decision model testing.

KNIME Business Hub finds application in data transformation, cleansing, and multi-source integration for analytics and reporting. Companies utilize it for predictive modeling, clustering, classification, machine learning, and automating workflows. Its coding-free approach suits educational and professional settings, assisting industries in data wrangling, ETLs, and prototyping decision models.

Knime

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

Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG

Buyer's Guide

Data Science Platforms

August 2025

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