We performed a comparison between Domino Data Science Platform and Microsoft Azure Machine Learning Studio based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."The scalability of the solution is good; I'd rate it four out of five."
"The most valuable feature of Microsoft Azure Machine Learning Studio is the ease of use for starting projects. It's simple to connect and view the results. Additionally, the solution works well with other Microsoft solutions, such as Power Automate or SQL Server. It is easy to use and to connect for analytics."
"The solution is scalable."
"In terms of what I found most valuable in Microsoft Azure Machine Learning Studio, I especially love the designer because you can just drag and drop items there and apply the logic that's already available with the designer. I love that I can use the libraries in Microsoft Azure Machine Learning Studio, so I don't have to search for the algorithms and all the relevant libraries because I can see them directly on the designer just by dragging and dropping. Though there's a bit of work during data cleansing, that's normal and can't be avoided. At least it's easy to find the relevant algorithm, apply that algorithm to the data, then get the desired output through Microsoft Azure Machine Learning Studio. I also like the API feature of the solution which is readily available for me to expose the output to any consuming application, so that takes out a lot of headache. Otherwise, I have to have a developer who knows the API, and I have to have an API app, so all that is completely taken care of by the Microsoft Azure Machine Learning Studio designer. With the solution, I can concentrate on how to improve the data quality to get quality recommendations, so this lets me concentrate on my job rather than focusing on the regular development of APIs or the pipelines, in particular, the data pipelines pulling the data from other sources. All the data is taken care of and you can also concentrate on other required auxiliary activities rather than just concentrating on machine learning."
"Visualisation, and the possibility of sharing functions are key features."
"It's easy to deploy."
"It is a scalable solution…It is a pretty stable solution…The solution's initial setup process was pretty straightforward."
"It's easy to use."
"The solution facilitates our production."
"The predictive analysis feature needs improvement."
"The platform's integration feature could be better."
"Operability with R could be improved."
"Using the solution requires some specific learning which can take some time."
"When you use different Microsoft tools, there are different pricing metrics. It doesn't make sense. The pricing metrics are quire difficult to understand and should be either clarified or simplified. It would help us sell the solution to customers."
"The solution's initial setup process is complicated."
"n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces."
"The price of the solution has room for improvement."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →
Earn 20 points
Domino Data Science Platform is ranked 17th in Data Science Platforms while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 22 reviews. Domino Data Science Platform is rated 7.0, while Microsoft Azure Machine Learning Studio is rated 7.6. On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Has a drag and drop feature and easier learning curve, but the number of algorithms available could still be improved". Domino Data Science Platform is most compared with Databricks, Amazon SageMaker, Dataiku Data Science Studio, Alteryx and Anaconda, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, Azure OpenAI, TensorFlow and Google Cloud AI Platform.
See our list of best Data Science Platforms vendors.
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.