We performed a comparison between Google Cloud Datalab and Microsoft Azure Machine Learning Studio 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 infrastructure is highly reliable and efficient, contributing to a positive experience."
"The APIs are valuable."
"All of the features of this product are quite good."
"Google Cloud Datalab is very customizable."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"The initial setup is very simple and straightforward."
"The most valuable feature of the solution is the availability of ChatGPT in the solution."
"The interface is very intuitive."
"Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most."
"It's a great option if you are fairly new and don't want to write too much code."
"It is a scalable solution…It is a pretty stable solution…The solution's initial setup process was pretty straightforward."
"Their web interface is good."
"The UI is very user-friendly and that AI is easy to use."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"The product must be made more user-friendly."
"The interface should be more user-friendly."
"We have also encountered challenges during our transition period in terms of data control and segmentation. The management of each channel and data structure as it has its own unique characteristics requires very detailed and precise control. The allocation should be appropriate and the complexity increases due to the different time zones and geographic locations of our clients. The process usually involves migrating the existing database sets to gcp and ensure data integrity is maintained. This is the only challenge that we faced while navigating the integers of the solution and honestly it was an interesting and unique experience."
"There is room for improvement in the graphical user interface. So that the initial user would use it properly, that would be a good option."
"Microsoft Azure Machine Learning Studio could improve by adding pixel or image analysis. This is a priority for me."
"Integration with social media would be a valuable enhancement."
"The data processor can pose a bit of a challenge, but the real complexity is determined by the skill of the implementation team."
"The initial setup time of the containers to run the experiment is a bit long."
"The speed of deployment should be faster, as should testing."
"There's room for improvement in terms of binding the integration with Azure DevOps."
"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."
"When you use different Microsoft tools, there are different pricing metrics. It doesn't make sense. The pricing metrics are quire difficult to understand and should be either clarified or simplified. It would help us sell the solution to customers."
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Google Cloud Datalab is ranked 14th in Data Science Platforms with 5 reviews while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 48 reviews. Google Cloud Datalab is rated 7.6, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Google Cloud Datalab writes "Easy to setup, stable and easy to design data pipelines". 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". Google Cloud Datalab is most compared with Databricks, IBM SPSS Statistics, Cloudera Data Science Workbench, IBM SPSS Modeler and Domino Data Science Platform, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, Azure OpenAI, TensorFlow and Google Cloud AI Platform. See our Google Cloud Datalab 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.