We performed a comparison between Databrick and Microsoft Azure Machine Learning Studio based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison of Results: Based on the parameters we compared, Microsoft Azure Machine Learning Studio seems to be a slightly superior solution. All other things being more or less equal, our reviewers found Databricks rather expensive to purchase. Some users also feel that Microsoft Azure Machine Learning Studio has better machine learning capabilities.
"The solution offers a free community version."
"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"
"The simplicity of development is the most valuable feature."
"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."
"The main features of the solution are efficiency."
"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
"Specifically for data science and data analytics purposes, it can handle large amounts of data in less time. I can compare it with Teradata. If a job takes five hours with Teradata databases, Databricks can complete it in around three to three and a half hours."
"Databricks is a unified solution that we can use for streaming. It is supporting open source languages, which are cloud-agnostic. When I do database coding if any other tool has a similar language pack to Excel or SQL, I can use the same knowledge, limiting the need to learn new things. It supports a lot of Python libraries where I can use some very easily."
"The drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"Microsoft Azure Machine Learning Studio is easy to use and deploy."
"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 easy to use and has good automation capabilities in conjunction with Azure DevOps."
"The solution is very easy to use, so far as our data scientists are concerned."
"It has helped in reducing the time involved for coding using R and/or Python."
"The solution is very fast and simple for a data science solution."
"The product's standout feature is a robust multi-file network with limited availability."
"I would like it if Databricks adopted an interface more like R Studio. When I create a data frame or a table, R Studio provides a preview of the data. In R Studio, I can see that it created a table with so many columns or rows. Then I can click on it and open a preview of that data."
"The product should provide more advanced features in future releases."
"The pricing of Databricks could be cheaper."
"Implementation of Databricks is still very code heavy."
"The integration of data could be a bit better."
"Databricks has added some alerts and query functionality into their SQL persona, but the whole SQL persona, which is like a role, needs a lot of development. The alerts are not very flexible, and the query interface itself is not as polished as the notebook interface that is used through the data science and machine learning persona. It is clunky at present."
"It would be nice to have more guidance on integrations with ETLs and other data quality tools."
"It should have more compatible and more advanced visualization and machine learning libraries."
"In terms of improvement, I'd like to have more ability to construct and understand the detailed impact of the variables on the model. Their algorithms are very powerful and they explain overall the net contribution of each of the variables to the solution. In terms of being able to say to people "If you did this, you'll get this much more improvement" it wasn't great."
"The AutoML feature is very basic and they should improve it by using a more robust algorithm."
"The product must improve its documentation."
"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."
"The speed of deployment should be faster, as should testing."
"The platform's integration feature could be better."
"The solution should be more customizable. There should be more algorithms."
"Enable creating ensemble models easier, adding more machine learning algorithms."
More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 52 reviews. Databricks is rated 8.2, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". 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". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Dremio and Azure Stream Analytics, whereas Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Azure OpenAI, TensorFlow, Google Cloud AI Platform and Dataiku. See our Databricks vs. Microsoft Azure Machine Learning Studio report.
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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.