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KNIME Business Hub vs Microsoft Azure Machine Learning Studio comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Feb 8, 2026

Review summaries and opinions

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

ROI

Sentiment score
5.6
KNIME Business Hub offers excellent ROI with low costs, ease of use, and encourages cost-effective experimentation before full-scale implementation.
Sentiment score
7.0
Microsoft Azure Machine Learning Studio improves efficiency with a 36% ROI, offering streamlined processes and comprehensive solutions.
I have seen a return on investment from using Microsoft Azure Machine Learning Studio in terms of workload reduction, as we now complete the same projects with two people instead of five.
Data Scientist
 

Customer Service

Sentiment score
6.5
KNIME Business Hub offers efficient support through community forums and documentation but needs more diverse language options and resources.
Sentiment score
7.2
Microsoft Azure Machine Learning Studio offers responsive support, but small clients suggest faster responses and improved escalation processes.
While they cannot always provide immediate answers, they are generally efficient and simplify tasks, especially in the initial phase of learning KNIME.
BI Analyst at a photography company with 11-50 employees
My mark for technical support for KNIME Business Hub is about a 7, as most of the support is in the community, and it is quite good because it is open source.
Senior Consultant at a tech vendor with 10,001+ employees
The customer support for Microsoft Azure Machine Learning Studio is quite responsive across different channels, making it a cool experience.
Data Scientist
Microsoft technical support is rated a seven out of ten.
Solution Sales Specialist at Intent Solutions Group
 

Scalability Issues

Sentiment score
6.7
KNIME Business Hub is scalable with server setups but faces challenges on desktops with large datasets and requires add-ons.
Sentiment score
7.4
Microsoft Azure Machine Learning Studio is praised for its scalability, flexibility, and efficient cloud-based capabilities, with high user satisfaction.
Microsoft Azure Machine Learning Studio is scalable as I can choose the compute, making it flexible for various scales.
Data Engineer at a educational organization with 201-500 employees
Microsoft Azure Machine Learning Studio's scalability has been beneficial, as I could increase my compute resources when needing more data injection.
Data Scientist
We are building Azure Machine Learning Studio as a scalable solution.
Senior Developer at a financial services firm with 10,001+ employees
 

Stability Issues

Sentiment score
7.6
Users find KNIME Business Hub stable, rating it 7-10/10, though noting crashes with large data and improved stability post-version 4.
Sentiment score
7.8
Microsoft Azure Machine Learning Studio is stable, reliable, with occasional JavaScript issues, suitable for non-production environments.
For now, KNIME Business Hub is excellent for me and for our team.
Co Founder & Chief Data Officer Cdo at NTT DATA
From 1 to 10, I would rate the stability of KNIME Business Hub quite good, around an 8 or 9.
Senior Consultant at a tech vendor with 10,001+ employees
 

Room For Improvement

KNIME Business Hub needs enhanced performance, data visualization, integration, and user interface improvements to handle large datasets effectively.
Users seek improved usability, algorithm variety, support, pricing, integration, deep learning modules, and better data preparation in Azure ML Studio.
I would like to see additional functions in KNIME Business Hub that can connect to generative AI, allowing users to describe the workflow for easier workflow generation and creation.
Senior Consultant at a tech vendor with 10,001+ employees
When I import this data set in the File Reader node, I have problems with this field because it is a date, but the problem is that it imports it as text.
Co Founder & Chief Data Officer Cdo at NTT DATA
Computer vision is the most important because now there is a new age of large language models and visual language models.
Director, Channel And Alliances at Basefy
It would be beneficial for them to incorporate more services required for LLMs or LLM evaluation.
Data Engineer at a educational organization with 201-500 employees
There is always room for improvement, and I expect Microsoft Azure Machine Learning Studio to continue iterating and focusing on a human-centric design approach.
Data Scientist
In future updates, I would appreciate improvements in integration and more AI features.
Public Cloud at KDDI Corporation
 

Setup Cost

KNIME Business Hub provides a cost-effective open-source desktop version, with server pricing based on enterprise support needs.
Microsoft Azure's pricing is seen as reasonable, though complexities and potential high costs require careful management.
I rate the pricing as three or four on a scale of one to ten in terms of affordability.
Solution Sales Specialist at Intent Solutions Group
The pricing for Microsoft Azure Machine Learning Studio is reasonable since it's pay as you go.
Data Scientist
 

Valuable Features

KNIME Business Hub simplifies data tasks with an intuitive interface, supporting automation, seamless integrations, and extensive machine learning tools.
Microsoft Azure Machine Learning Studio is user-friendly, scalable, integrates with Azure, supports AutoML, and accommodates all skill levels.
It is more elastic and modern compared to SAP Data Services, allowing node creation and regrouping components or steps for reuse in different projects.
BI Analyst at a photography company with 11-50 employees
KNIME is more intuitive and easier to use, which is the principal advantage.
Student at ISCTE - INSTITUTO UNIVERSITÁRIO DE LISBOA
Collection of company-wide information is one of the main benefits that KNIME Business Hub provides to the end users; all the intellectual property that has been developed in a central location is critical.
Director, Channel And Alliances at Basefy
The platform provides managed services and compute, and I have more control in Azure, even in terms of monitoring services.
Data Engineer at a educational organization with 201-500 employees
Microsoft Azure Machine Learning Studio is a powerful platform for those already in the Azure ecosystem because it allows for scalability and provides a good environment for reproducibility, as well as collaboration tools, all designed and packaged in one place, which makes it outstanding.
Data Scientist
Azure Machine Learning Studio provides a platform to integrate with large language models.
Senior Developer at a financial services firm with 10,001+ employees
 

Categories and Ranking

KNIME Business Hub
Ranking in Data Science Platforms
3rd
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
63
Ranking in other categories
Data Mining (1st)
Microsoft Azure Machine Lea...
Ranking in Data Science Platforms
7th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
62
Ranking in other categories
AI Development Platforms (5th)
 

Mindshare comparison

As of May 2026, in the Data Science Platforms category, the mindshare of KNIME Business Hub is 5.6%, down from 11.9% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 3.0%, down from 5.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
KNIME Business Hub5.6%
Microsoft Azure Machine Learning Studio3.0%
Other91.4%
Data Science Platforms
 

Featured Reviews

NataliaRaffo - PeerSpot reviewer
Co Founder & Chief Data Officer Cdo at NTT DATA
Workflow automation has accelerated advanced analytics and machine learning delivery
Sometimes it is a little bit difficult to use some nodes when we have many large-scale data, for example, CSV files with a large amount of data. It is sometimes difficult to try to import the data in KNIME Business Hub nodes because I think that some features that are in the CSV in text, for example, large text, is difficult for KNIME Business Hub to import these fields. I don't know why, but it is very difficult. We need to try to use different nodes for importing the data, such as File Reader and CSV Reader. However, I think that it is always the features that have much text, it is difficult for KNIME Business Hub to understand and import this information. I don't know why, or maybe I don't know if we don't know what the better option is to configure the node to import all the CSV or the data set. However, we have always had this problem. In some nodes, sometimes it is the same because sometimes, for example, I have a CSV and in my CSV, I have a feature that is, for example, a date. When I import this data set in the File Reader node, I have problems with this field because it is a date, but the problem is that it imports it as text, for example. We try to use their nodes that convert text to date, but sometimes it is difficult, and it is not immediate to transform the text into a date. So we needed to convert the text into a date in the CSV, and then import it again in the KNIME Business Hub node and try to have a good read of this field. I know that KNIME Business Hub has some nodes to convert text to date and others, but sometimes it is difficult to use these nodes. I don't know why. Maybe it needs a specific format for the date and we need to transform our feature in this option. So sometimes it is a large process to convert these features. However, sometimes we need to investigate and search for other nodes, and try with other nodes to import these cases.
reviewer2722962 - PeerSpot reviewer
Data Scientist
Platform accelerates model development, enhances collaboration, and offers efficient deployment
The best features Microsoft Azure Machine Learning Studio offers include deep integration with Python notebooks and Azure Data Lake, which allows me to import external data, and through the pipeline, I can build my models, performing what is called data injection for my model building, making that deep integration quite interesting to use. Microsoft Azure Machine Learning Studio is a powerful platform for those already in the Azure ecosystem because it allows for scalability and provides a good environment for reproducibility, as well as collaboration tools, all designed and packaged in one place, which makes it outstanding. Microsoft Azure Machine Learning Studio has positively impacted my organization by reducing our project delivery times and increasing the pace at which we work, allowing us to focus on other more important tasks. Using Microsoft Azure Machine Learning Studio has reduced our model development time from approximately four hours to about two hours.
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Manufacturing Company
9%
University
8%
Educational Organization
7%
Financial Services Firm
13%
Manufacturing Company
8%
Performing Arts
7%
Computer Software Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business21
Midsize Enterprise16
Large Enterprise31
By reviewers
Company SizeCount
Small Business23
Midsize Enterprise6
Large Enterprise30
 

Questions from the Community

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?
In my previous PeerSpot review from March 2024, I mentioned that KNIME was not very strong in visualization and that I wanted to see NLQ (Natural Language Query) and automated visualization capabil...
What is your primary use case for KNIME?
I mainly use KNIME for ETL and data integration projects, followed by clustering and customer segmentation, process mining, AI and machine learning preprocessing pipelines, and recently GenAI orche...
Which do you prefer - Databricks or Azure Machine Learning Studio?
Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...
What do you like most about Microsoft Azure Machine Learning Studio?
The learning curve is very low. Operationalizing the model is also very easy within the Azure ecosystem.
What is your experience regarding pricing and costs for Microsoft Azure Machine Learning Studio?
The pricing for Microsoft Azure Machine Learning Studio is reasonable since it's pay as you go, meaning it won't cost excessively unless specific resources are used.
 

Also Known As

KNIME Analytics Platform
Azure Machine Learning, MS Azure Machine Learning Studio
 

Overview

 

Sample Customers

Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Walgreens Boots Alliance, Schneider Electric, BP
Find out what your peers are saying about KNIME Business Hub vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: April 2026.
893,244 professionals have used our research since 2012.