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Dataiku vs KNIME Business Hub comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 27, 2025

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
KNIME Business Hub
Ranking in Data Science Platforms
3rd
Average Rating
8.2
Reviews Sentiment
7.1
Number of Reviews
60
Ranking in other categories
Data Mining (1st)
 

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 KNIME Business Hub is 12.3%, up from 10.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
KNIME Business Hub12.3%
Dataiku12.3%
Other75.4%
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
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,

Quotes from Members

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

Pros

"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"I believe the return on investment looks positive."
"The most valuable feature is the set of visual data preparation tools."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"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."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"The solution is quite stable."
"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."
"This open-source product can compete with category leaders in ELT software."
"I've never had any problems with stability."
"KNIME is easy to learn."
"It's a huge tool with machine learning features as well."
"The tool's analytic capabilities are good."
"From a user-friendliness perspective, it's a great tool."
"The solution allows for sharing model designs and model operations with other data analysts."
"Overall KNIME serves its purpose and does a good job."
 

Cons

"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"The license is very expensive."
"The ability to have charts right from the explorer would be an improvement."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"There is room for improvement in terms of allowing for more code-based features."
"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"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."
"The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R)."
"Sometimes, we needed more space to handle larger operations, especially since our machines had limited space and memory due to Kubernetes clusters."
"The dynamic column name feature could be improved. When attempting to automate processes involving columns, such as with companies, it becomes difficult to achieve the same result when we make changes."
"The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"For graphics, the interface is a little confusing. So, this is a point that could be improved."
"The program is not fit for handling very large files or databases (greater than 1GB); it gets too slow and has a tendency to crash easily."
 

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."
"We're using the free academic license just locally. I went for KNIME because they have a free academic license."
"KNIME is an open-source tool, so it's free to use."
"KNIME offers a free version"
"It is free of cost. It is GNU licensed."
"For beginners, the free desktop version is very attractive, but the full server version can be more expensive. I have only used the free version and it offers a fair pricing system. I have been promoting it to others without any compensation or request from the company, simply because I am enthusiastic about it. I am not aware of the pricing for the server version, but it seems to be widely used."
"There is no cost for using KNIME because it is an open-source solution, but you have to pay if you need a server."
"While there are certain limitations in functionality, you can still utilize it efficiently free of charge."
"The client versions are mostly free, and we pay only for the KNIME server version. It's not a cheap solution."
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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
10%
Manufacturing Company
10%
University
9%
Computer Software Company
8%
 

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 Business20
Midsize Enterprise16
Large Enterprise29
 

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 KNIME?
Since KNIME is a no-code platform, it is easy to work with.
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.
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 version, 5.4, when it becomes available. The machine learning and profileration asp...
 

Also Known As

Dataiku DSS
KNIME Analytics Platform
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Find out what your peers are saying about Dataiku vs. KNIME Business Hub and other solutions. Updated: July 2025.
867,445 professionals have used our research since 2012.