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."
"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."
"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."
"It is a scalable solution…It is a pretty stable solution…The solution's initial setup process was pretty straightforward."
"The solution facilitates our production."
"The solution is very easy to use, so far as our data scientists are concerned."
"Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most."
"The initial setup is very simple and straightforward."
"I find Microsoft Azure Machine Learning Studio advantageous because it allows integration with Titan Scratch and offers an easy-to-use drag-and-drop menu for developing machine learning models."
"The drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"When you import the dataset you can see the data distribution easily with graphics and statistical measures."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
"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."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"Overall, the icons in the solution could be improved to provide better guidance to users. Additionally, the setup process for the solution could be made easier."
"Microsoft should also include more examples and tutorials for using this product."
"It is not easy. It is a complex solution. It takes some time to get exposed to all the concepts. We're trying to have a CI/CD pipeline to deploy a machine learning model using negative actions. It was not easy. The components that we're using might have something to do with this."
"The data cleaning functionality is something that could be better and needs to be improved."
"In terms of data capabilities, if we compare it to Google Cloud's BigQuery, we find a difference. When fetching data from web traffic, Google can do a lot of processing with small queries or functions."
"There's room for improvement in terms of binding the integration with Azure DevOps."
"The regulatory requirements of the product need improvement."
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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 53 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, TensorFlow and Google Cloud AI Platform. See our DataRobot vs. Microsoft Azure Machine Learning Studio report.
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