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Compare KNIME vs. Microsoft Azure Machine Learning Studio

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Featured Review
Find out what your peers are saying about KNIME vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: November 2021.
552,407 professionals have used our research since 2012.
Quotes From Members

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

"The visual workflow tools for custom and complex tasks always beat raw coding languages with the agility, speed to deliver, and ease of subsequent changes.""This solution is easy to use and it can be used to create any kind of model.""It can handle an unlimited amount of data, which is the advantage of using Knime.""KNIME is quite scalable, which is one of the most important features that we found.""This open-source product can compete with category leaders in ELT software.""It is very fast to develop solutions.""The solution is good for teaching, since there is no need to code.""What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."

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"It's good for citizen data scientists, but also, other people can use Python or .NET code.""The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.""The UI is very user-friendly and that AI is easy to use.""The most valuable feature is data normalization.""The solution is very fast and simple for a data science solution.""The AutoML is helpful when you're starting to explore the problem that you're trying to solve.""It's a great option if you are fairly new and don't want to write too much code.""The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout."

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"It could input more data acquisitions from other sources and it is difficult to combine with Python.""They should look at other vendors like Alteryx that are more user friendly and modern.""There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool.""Both RapidMiner and KNIME should be made easier to use in the field of deep learning.""Compared to the other data tools on the market, the user interface can be improved.""If they had a more structured training model it would be very helpful.""There should be better documentation and the steps should be easier.""From the point of view of the interface, they can do a little bit better."

More KNIME Cons »

"In terms of improvement, I'd like to have more ability to construct and understand the detailed impact of the variables on the model. Their algorithms are very powerful and they explain overall the net contribution of each of the variables to the solution. In terms of being able to say to people "If you did this, you'll get this much more improvement" it wasn't great.""The data processor can pose a bit of a challenge, but the real complexity is determined by the skill of the implementation team.""A problem that I encountered was that I had to pay for the model that I wanted to deploy and use on Azure Machine Learning, but there wasn't any option that that model can be used in the designer.""The solution should be more customizable. There should be more algorithms.""Integration with social media would be a valuable enhancement.""I think they should improve two things. They should make their user interface more user-friendly. Integration could also be better. Because Microsoft Machine Learning is a Microsoft product, it's fully integrated with Microsoft Azure but not fully supported for other platforms like IBM or AWS or something else.""The AutoML feature is very basic and they should improve it by using a more robust algorithm.""n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces."

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Pricing and Cost Advice
"This is an open-source solution that is free to use.""The price for Knime is okay.""The price of KNIME is quite reasonable and the designer tool can be used free of charge.""It's an open-source solution.""KNIME assets are stand alone, as the solution is open source.""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.""At this time, I am using the free version of Knime.""There is a Community Edition and paid versions available."

More KNIME Pricing and Cost Advice »

"From a developer's perspective, I find the price of this solution high.""The licensing cost is very cheap. It's less than $50 a month.""There is a license required for this solution.""I am paying for it following a pay-as-you-go. So, the more I use it, the more it costs."

More Microsoft Azure Machine Learning Studio Pricing and Cost Advice »

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Questions from the Community
Top Answer: I was able to apply basic algorithms through just dragging and dropping.
Top Answer: KNIME assets are stand alone, as the solution is open source. I have not looked into their enterprise level application costs. While cost is a parameter, I would definitely consider other options… more »
Top Answer: I would prefer to have more connectivity. The user documentation is insufficient. I would like to see more enterprise level application. There are high end features which should appear, the MLOps… more »
Top Answer: 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… more »
Top Answer: The initial setup is very simple and straightforward.
Top Answer: The licensing cost is very cheap. It's less than $50 a month would costs for multiple users.
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Average Words per Review
Also Known As
KNIME Analytics Platform
Azure Machine Learning, MS Azure Machine Learning Studio
Learn More
KNIME is the leading open platform for data-driven innovation helping organizations to stay ahead of change. Use our open-source, enterprise-grade analytics platform to discover the potential hidden in your data, mine for fresh insights or predict new futures.

Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.

It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.

Learn more about KNIME
Learn more about Microsoft Azure Machine Learning Studio
Sample Customers
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Walgreens Boots Alliance, Schneider Electric, BP
Top Industries
Comms Service Provider15%
Comms Service Provider22%
Computer Software Company19%
Financial Services Firm8%
Manufacturing Company8%
Financial Services Firm14%
Recruiting/Hr Firm14%
Computer Software Company14%
Energy/Utilities Company14%
Computer Software Company24%
Comms Service Provider18%
Energy/Utilities Company6%
Manufacturing Company6%
Company Size
Small Business32%
Midsize Enterprise32%
Large Enterprise36%
Small Business32%
Midsize Enterprise11%
Large Enterprise57%
Small Business30%
Midsize Enterprise10%
Large Enterprise60%
Find out what your peers are saying about KNIME vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: November 2021.
552,407 professionals have used our research since 2012.

KNIME is ranked 3rd in Data Science Platforms with 15 reviews while Microsoft Azure Machine Learning Studio is ranked 4th in Data Science Platforms with 16 reviews. KNIME is rated 8.2, while Microsoft Azure Machine Learning Studio is rated 7.8. The top reviewer of KNIME writes "Has good machine learning and big data connectivity but the scheduler needs improvement ". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Has the ability to do templating and transfer it so that we can do multiple types of models and data mining". KNIME is most compared with Alteryx, RapidMiner, Databricks, Weka and IBM SPSS Modeler, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Dataiku Data Science Studio, IBM Watson Studio, Alteryx and H2O.ai. See our KNIME vs. Microsoft Azure Machine Learning Studio report.

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We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.