Compare Domino Data Science Platform vs. Microsoft Azure Machine Learning Studio

Domino Data Science Platform is ranked 17th in Data Science Platforms with 1 review while Microsoft Azure Machine Learning Studio is ranked 6th in Data Science Platforms with 8 reviews. Domino Data Science Platform is rated 7.0, while Microsoft Azure Machine Learning Studio is rated 7.2. The top reviewer of Domino Data Science Platform writes "Good scalability and stability but the predictive analysis feature needs improvement". 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". Domino Data Science Platform is most compared with Amazon SageMaker, Databricks and Dataiku Data Science Studio, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Alteryx and Amazon SageMaker.
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Most Helpful Review
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Find out what your peers are saying about Alteryx, Knime, IBM and others in Data Science Platforms. Updated: December 2019.
390,232 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
The scalability of the solution is good; I'd rate it four out of five.

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The most valuable feature is data normalization.The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure.Visualisation, and the possibility of sharing functions are key features.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.When you import the dataset you can see the data distribution easily with graphics and statistical measures.Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most.MLS allows me to set up data experiments by running through various regression and other machine learning algorithms, with different data cleaning and treatment tools. All of this can be achieved via drag and drop, and a few clicks of the mouse.

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Cons
The predictive analysis feature needs improvement.

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The data cleaning functionality is something that could be better and needs to be improved.Integration with social media would be a valuable enhancement.If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice.Operability with R could be improved.I would like to see modules to handle Deep Learning frameworks.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.Enable creating ensemble models easier, adding more machine learning algorithms.​It could use to add some more features in data transformation, time series and the text analytics section.

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Pricing and Cost Advice
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From a developer's perspective, I find the price of this solution high.When we got our first models and were ready for the user acceptance testing, our licensing fees were between €2,500 ($2,750 USD) and €3,000 ($3,300 USD) monthly.To use MLS is fairly cheap. Even the paid account is something like $20/month, unless you are provisioning large numbers of VMs for a Hadoop cluster. The main MS makes money with this solution is forcing the user to deploy their model on REST API, and being charged each time the API is accessed. There are several pricing tiers for the API. If you do not use the API, then value of MLS is to create rapid experiments ($20/month). The resulting model is not exportable to use, thus you’ll have to recreate the algorithms in either R or Python, which is what I did. MLS results gave me a direction to work with, the actual work is mostly done in R and Python outside of MLS.

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Ranking
17th
Views
2,641
Comparisons
2,001
Reviews
1
Average Words per Review
164
Avg. Rating
7.0
6th
Views
9,703
Comparisons
8,066
Reviews
8
Average Words per Review
479
Avg. Rating
7.3
Top Comparisons
Also Known As
Domino Data Lab PlatformAzure Machine Learning
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Domino Data Lab
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Microsoft
Overview

Domino provides a central system of record that keeps track of all data science activity across an organization. Domino helps data scientists seamlessly orchestrate AWS hardware and software toolkits, increase flexibility and innovation, and maintain required IT controls and standards. Organizations can automatically keep track of all data, tools, experiments, results, discussion, and models, as well as dramatically scale data science investments and impact decision-making across divisions. The platform helps organizations work faster, deploy results sooner, scale rapidly, and reduce regulatory and operational risk.

Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.

It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.

Offer
Learn more about Domino Data Science Platform
Learn more about Microsoft Azure Machine Learning Studio
Sample Customers
Allstate, Tesla, Dell, Moody's Analytics, SurveyMonkey, Eventbrite, Carnival
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Top Industries
VISITORS READING REVIEWS
Software R&D Company40%
Financial Services Firm11%
Manufacturing Company9%
Transportation Company5%
VISITORS READING REVIEWS
Software R&D Company31%
Comms Service Provider18%
Manufacturing Company6%
Media Company5%
Find out what your peers are saying about Alteryx, Knime, IBM and others in Data Science Platforms. Updated: December 2019.
390,232 professionals have used our research since 2012.
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