We performed a comparison between Microsoft Azure Machine Learning Studio and RapidMiner 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 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."
"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."
"The solution is very easy to use, so far as our data scientists are concerned."
"The solution is integrated with our Microsoft Azure tenant, and we don't have to go anywhere else outside the tenant."
"Azure's AutoML feature is probably better than the competition."
"It is very easy to test different kinds of machine-learning algorithms with different parameters. You choose the algorithm, drag and drop to the workspace, and plug the dataset into this component."
"I've been using a lot of components from the Strategic Extension and Python Extension."
"The data science, collaboration, and IDN are very, very strong."
"RapidMiner is very easy to use."
"The most valuable feature is what the product sets out to do, which is extracting information and data."
"I like not having to write all solutions from code. Being able to drag and drop controls, enables me to focus on building the best model, without needing to search for syntax errors or extra libraries."
"It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive."
"What I like about RapidMiner is its all-in-one nature, which allows me to prepare, extract, transform, and load data within the same tool."
"The solution is stable."
"Microsoft Azure Machine Learning Studio could improve in providing more efficient and cost-effective access to its tools for companies like mine."
"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 solution should be more customizable. There should be more algorithms."
"Technical support could improve their turnaround time."
"The platform's integration feature could be better."
"In the Machine Learning Studio, particularly the Designer part, which is essentially Azure's demo designer, there is room for improvement. Many customers and users tend to switch to Microsoft Azure Multi-Joiners, which is a more basic version, but they do so internally. One area that could use enhancement is the process of connecting components. Currently, every time you want to connect a component, such as linking it to your storage or an instance like EC2, you have to input your username and password repeatedly. This can be quite cumbersome. Google, for instance, has made it more user-friendly by allowing easy access for connecting services within a workspace. In a workspace, you can set up various resources like storage, a database cluster, machine learning studio, and more. When connecting these services, there's no need to enter your username and password each time, making it a more efficient process. Another aspect to consider is the role of the designer, and they were to integrate a large language model to handle various tasks, it could significantly enhance the overall scalability and usability of the platform."
"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."
"Using the solution requires some specific learning which can take some time."
"I think that they should make deep learning models easier."
"Improve the online data services."
"I would like to see more integration capabilities."
"RapidMiner can improve deep learning by enhancing the features."
"One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome this hurdle, I believe RapidMiner could improve by providing more tutorials tailored for new users."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
"If they could include video tutorials, people would find that quite helpful."
"In the Mexican or Latin American market, it's kind of pricey."
More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →
Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 53 reviews while RapidMiner is ranked 6th in Data Science Platforms with 20 reviews. Microsoft Azure Machine Learning Studio is rated 7.6, while RapidMiner is rated 8.6. 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 RapidMiner writes "A no-code tool that helps to build machine learning models ". Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and Anaconda, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku, Tableau and IBM SPSS Modeler. See our Microsoft Azure Machine Learning Studio vs. RapidMiner report.
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