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Domino Data Science Platform 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

Domino Data Science Platform
Ranking in Data Science Platforms
17th
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
2
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 October 2025, in the Data Science Platforms category, the mindshare of Domino Data Science Platform is 2.6%, down from 2.9% compared to the previous year. The mindshare of KNIME Business Hub is 11.9%, 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 Hub11.9%
Domino Data Science Platform2.6%
Other85.5%
Data Science Platforms
 

Featured Reviews

AS
Accelerated machine learning model development with seamless deployment
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar to using Git. Each user operates on their own equivalent of a branch or fork, and once finished, they…
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

"The scalability of the solution is good; I'd rate it four out of five."
"The workspaces, which are like wrappers of Docker containers, made it easy to start development environments using Domino."
"Easy to use, stable, and powerful."
"It can handle an unlimited amount of data, which is the advantage of using Knime."
"It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured."
"This solution is easy to use and it can be used to create any kind of model."
"The solution is good for teaching, since there is no need to code."
"I know I don't use it to its full capacity, but I love the Rule Engine feature. It has allowed me to create lookup tables on the fly and break down text fields into quantifiable data."
"It allows for a user-friendly approach where you can simply drag and drop elements to create your model, which is a convenient and effective idea."
"The product is open-source and therefore free to use."
 

Cons

"The deployment of large language models (LLMs) could be improved."
"The predictive analysis feature needs improvement."
"KNIME's documentation is not strong."
"They could add more detailed examples of the functionality of every node, how it works and how we can use it, to make things easier at the beginning."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"KNIME can improve by adding more automation tools in the query, similar to UiPath or Blue Prism. It would make the data collection and cleanup duties more versatile."
"Occasionally, when using the GET object, there might be issues due to the velocity of the lines or the IT system of the commission."
"The documentation needs a proper rework. ​"
"The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data."
"If they had a more structured training model it would be very helpful."
 

Pricing and Cost Advice

Information not available
"KNIME is free as a stand-alone desktop-based platform but if you want to get a KNIME server then you can find the cost on their website."
"I use the open-source version."
"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."
"KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required."
"While there are certain limitations in functionality, you can still utilize it efficiently free of charge."
"It's an open-source solution."
"It is free of cost. It is GNU licensed."
"This is an open-source solution that is free to use."
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Top Industries

By visitors reading reviews
Financial Services Firm
39%
Manufacturing Company
9%
Insurance Company
8%
Healthcare Company
5%
Financial Services Firm
11%
University
9%
Manufacturing Company
9%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business20
Midsize Enterprise16
Large Enterprise29
 

Questions from the Community

What needs improvement with Domino Data Science Platform?
The deployment of large language models (LLMs) could be improved. Currently, Domino provides a simple server that cannot handle big deployments, which is not suitable for LLMs.
What is your primary use case for Domino Data Science Platform?
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar...
What advice do you have for others considering Domino Data Science Platform?
It's important to have a DevOps team well-versed with cloud-native solutions to manage Domino effectively. Relying solely on data scientists might not be sufficient. I'd rate the solution eight out...
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

Domino Data Lab Platform
KNIME Analytics Platform
 

Interactive Demo

Demo not available
 

Overview

 

Sample Customers

Allstate, GSK, AstraZeneca, Federal Reserve, US Navy, Bristol Myers Squibb, Bayer, BNP Paribas, Moodys, New York Life
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Find out what your peers are saying about Domino Data Science Platform vs. KNIME Business Hub and other solutions. Updated: September 2025.
870,697 professionals have used our research since 2012.