We performed a comparison between Microsoft Azure Machine Learning Studio and Saturn Cloud based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The learning curve is very low. Operationalizing the model is also very easy within the Azure ecosystem."
"It's good for citizen data scientists, but also, other people can use Python or .NET code."
"What I like best about Microsoft Azure Machine Learning Studio is that it's a straightforward tool and it's easy to use. Another valuable feature of the tool is AutoML which lets you get better metrics to train the model right and with good accuracy. The AutoML feature allows you to simply put in your data, and it'll pre-process and create a more accurate model for you. You don't have to do anything because AutoML in Microsoft Azure Machine Learning Studio will take care of it."
"The solution is really 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."
"The drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses."
"Visualisation, and the possibility of sharing functions are key features."
"There is plenty of computational resources (both GPU, CPU and disk space)."
"The feature I like the most about Saturn Cloud is that it has lightning-fast CPUs."
"Saturn Cloud supports GPU as part of the environment, which is essential for many computational tasks in machine learning projects. It also allows us to edit the environment, including the image, before we start the cloud resources. This feature lets us quickly set up the environment without the hassle of moving the data and code to another cloud device."
"It offered an excellent development environment while not touching our production cloud resources."
"It didn't take long to see that Saturn Cloud could scale with my needs, providing more resources when required."
"n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces."
"I personally would prefer if data could be tunneled to my model through a SAP ERP system, and have features of Excel, such as Pivot Tables, integrated."
"The regulatory requirements of the product need improvement."
"Technical support could improve their turnaround time."
"The price of the solution has room for improvement."
"Microsoft Azure Machine Learning Studio could improve in providing more efficient and cost-effective access to its tools for companies like mine."
"In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data."
"It would be great if the solution integrated Microsoft Copilot, its AI helper."
"Public Clouds integration and sandbox environments would be a true game changer."
"Providing more detailed and beginner-friendly documentation, especially for advanced features, could greatly enhance the user experience."
"Saturn Cloud should include prebuilt images for advanced data science packages like LightGBM in the next release. If possible, they should also provide a Kaggle image, which contains the most common Python packages used in machine learning."
"It would be nice to have more hardware category options, like TPU coprocessors or ARM64 CPUs."
"We'd like to have the capability for installing more libraries."
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Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 51 reviews while Saturn Cloud is ranked 8th in Data Science Platforms with 5 reviews. Microsoft Azure Machine Learning Studio is rated 7.6, while Saturn Cloud is rated 10.0. The top reviewer of Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". On the other hand, the top reviewer of Saturn Cloud writes "Great support, good availability, and seamless integration capabilities". Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and Google Cloud AI Platform, whereas Saturn Cloud is most compared with Amazon SageMaker and Remote Desktop with Multi-user support by Aurora. See our Microsoft Azure Machine Learning Studio vs. Saturn Cloud report.
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