We performed a comparison between DataRobot and Microsoft Azure Machine Learning Studio based on real PeerSpot user reviews.
Find out in this report how the two AI Development Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."DataRobot can be easy to use."
"It's easy to do MLOps operations. It's a lot easier to manage jobs and see the logs if there's any drift in a model."
"We especially like the initial part of feature engineering, because feature engineering is included in most engines, but DataRobot has an excellent way of picking up the right features."
"One of the notable advantages is that it offers both a visual designer, which is user-friendly, and an advanced coding option."
"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."
"It's easy to use."
"I like that it's totally easy to use. They have an AutoML solution, and their machine learning model is highly accurate. They also have a feature that can explain the machine learning model. This makes it easy for me to understand that model."
"Azure Machine Learning Studio's most valuable features are the package from Azure AutoML. It is quite powerful compared to the building of ML in Databricks or other AutoMLs from other companies, such as Google and Amazon."
"It is a scalable solution…It is a pretty stable solution…The solution's initial setup process was pretty straightforward."
"Its ability to publish a predictive model as a web based solution and integrate R and python codes are amazing."
"Their support is helpful."
"If we could include our existing Python or R code in DataRobot, we could make it even better. The DataRobot that we have is specific to an industry, but most of the time we would have our own algorithms, which are specific to our own use case. If we had a way by which we could integrate our proprietary things into DataRobot with a simple integration, it would help us a lot."
"The business departments will love to work with DataRobot because they use the tool to investigate their data, such as targeting what they want to investigate. They don't need any data scientists near them. They can investigate at eye level and bring into the BI tool, or can bring it to the data scientist. Data scientists can use this tool to bring increase the solution to the maximum. All the others can use it, but not to the maximum."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
"In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data."
"Operability with R could be improved."
"Microsoft Azure Machine Learning Studio worked okay for me, so right now, I don't have any room for improvement in mind for it. What I'd like added to Microsoft Azure Machine Learning Studio in its next version is a categorization for use cases or a template that makes the use cases simple to map out, for example, for healthcare, medical, or finance use cases, etc. This would be very helpful for users of Microsoft Azure Machine Learning Studio, especially for beginners."
"While ML Studio does give you the ability to run a lot of transformations, it struggles when the transformations are a bit more complex, when your entire process is transformation-heavy."
"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."
"In future releases, I would like to see better integration with Power BI within Microsoft Azure Machine Learning Studio."
"The AutoML feature is very basic and they should improve it by using a more robust algorithm."
"The price of the solution has room for improvement."
More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →
DataRobot is ranked 13th in AI Development Platforms with 3 reviews while Microsoft Azure Machine Learning Studio is ranked 1st in AI Development Platforms with 54 reviews. DataRobot is rated 8.6, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of DataRobot writes "Easy to manage jobs and see the logs if there's any drift in a model, user-friendly, and the data munching is fast". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". DataRobot is most compared with Amazon SageMaker, RapidMiner, Datadog, Alteryx and SAS Predictive Analytics, whereas Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI and TensorFlow. See our DataRobot vs. Microsoft Azure Machine Learning Studio report.
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