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Databricks vs Microsoft Azure Machine Learning Studio comparison

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Comparison Summary
Question: Which do you prefer - Databricks or Azure Machine Learning Studio?
Answer: Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with MLFlow. It allows for migration from one environment to another with tremendous ease. This solution is very scalable and can process large amounts of data very quickly. It is also very user-friendly, as not a lot of knowledge is needed to run it. As this solution is cloud-based, start-up time is easy and super fast. Azure Machine Learning Studio offers ready-made data samples and has some very useful modeling parameter settings. They offer courses and certifications within the solution, which makes it very attractive and beneficial for many users. This solution is very easy to use for teams with less experience and for those that are just getting started with the ML experience. This is really an amazing low-code/no-code solution. The solution is very scalable, with great flexibility. Databricks needs samples and templates for users to see exactly what the solution can do. Overall integration with other products could be better, and many times the error messages we have received have been vague and ambiguous, making it challenging to debug and thereby slowing down the overall process. Databricks can also be very costly as one scales up. Microsoft Machine Learning Studio offers limited customizations; a greater selection of algorithms is needed. If you want to go beyond the Microsoft Azure ecosystem, this may not be the best solution for you, as migration with other products can prove problematic. Conclusions Databricks and Azure Machine Learning Studio are both excellent, highly-regarded solutions. As our enterprise needs are very diverse, we found that each of these solutions offers attractive options that we can use simultaneously in successfully meeting our overall client needs.
Featured Review
Find out what your peers are saying about Databricks vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: January 2022.
563,327 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
"Ability to work collaboratively without having to worry about the infrastructure.""I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job.""The initial setup is pretty easy.""Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data.""The fast data loading process and data storage capabilities are great.""It's easy to increase performance as required.""One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often.""The solution is easy to use and has a quick start-up time due to being on the cloud."

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"The solution is very easy to use, so far as our data scientists are concerned.""The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.""It's good for citizen data scientists, but also, other people can use Python or .NET code.""The interface is very intuitive.""I like that it's totally easy to use. They have an AutoML solution, and their machine learning model is highly accurate. They also have a feature that can explain the machine learning model. This makes it easy for me to understand that model.""It's a great option if you are fairly new and don't want to write too much code.""The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout.""The most valuable feature is its compatibility with Tensorflow."

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Cons
"Anyone who doesn't know SQL may find the product difficult to work with.""The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration.""The integration of data could be a bit better.""Pricing is one of the things that could be improved.""Overall it's a good product, however, it doesn't do well against any individual best-of-breed products.""There are no direct connectors — they are very limited.""A lot of people are required to manage this solution.""The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."

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"It would be nice if the product offered more accessibility in general.""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.""They should have a desktop version to work on the platform.""n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces.""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.""There should be data access security, a role level security. Right now, they don't offer this.""The data processor can pose a bit of a challenge, but the real complexity is determined by the skill of the implementation team.""I have found Databricks is a better solution because it has a lot of different cluster choices and better integration with MLflow, which is much easier to handle in a machine learning system."

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Pricing and Cost Advice
  • "Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."
  • "We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
  • "The pricing depends on the usage itself."
  • "I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
  • "The price is okay. It's competitive."
  • "Databricks uses a price-per-use model, where you can use as much compute as you need."
  • "There are different versions."
  • "The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."
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  • "The licensing cost is very cheap. It's less than $50 a month."
  • "There is a license required for this solution."
  • "I am paying for it following a pay-as-you-go. So, the more I use it, the more it costs."
  • More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →

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    Questions from the Community
    Top Answer: 
    Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with… more »
    Top Answer: 
    We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It… more »
    Top Answer: 
    Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their… more »
    Top Answer: 
    The initial setup is very simple and straightforward.
    Top Answer: 
    The licensing cost is very cheap. It's less than $50 a month would costs for multiple users.
    Top Answer: 
    It's the first software that I've used in terms of machine learning. Therefore, I don't have anything to compare it to, however, it was okay for me. I didn't have any problems or anything. Maybe it… more »
    Ranking
    2nd
    Views
    30,779
    Comparisons
    25,469
    Reviews
    22
    Average Words per Review
    531
    Rating
    7.9
    4th
    Views
    16,529
    Comparisons
    13,221
    Reviews
    14
    Average Words per Review
    484
    Rating
    7.7
    Comparisons
    Also Known As
    Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
    Azure Machine Learning, MS Azure Machine Learning Studio
    Learn More
    Overview

    Databricks creates a Unified Analytics Platform that accelerates innovation by unifying data science, engineering, and business. It utilizes Apache Spark to help clients with cloud-based big data processing. It puts Spark on “autopilot” to significantly reduce operational complexity and management cost. The Databricks I/O module (DBIO) improves the read and write performance of Apache Spark in the cloud. An increase in productivity is ensured through Databricks’ collaborative workplace.

    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.

    Microsoft Azure Machine Learning Will Help You:

    • Rapidly build and train models
    • Operationalize at scale
    • Deliver responsible solutions
    • Innovate on a more secure hybrid platform

    With Microsoft Azure Machine Learning You Can:

    • Prepare data: Microsoft Azure Machine Learning Studio offers data labeling, data preparation, and datasets.
    • Build and train models: Includes notebooks, Visual Studio Code and Github, Automated ML, Compute instance, a drag-and-drop designer, open-source libraries and frameworks, customizable dashboards, and experiments
    • Validate and deploy: Manage endpoints, automate machine learning workflows (pipeline CI/CD), optimize models, access pre-built container images, share and track models and data, train and deploy models across multi-cloud and on-premises.
    • Manage and monitor: Track, log, and analyze data, models, and resources; Detect drift and maintain model accuracy; Trace ML artifacts for compliance; Apply quota management and automatic shutdown; Leverage built-in and custom policies for compliance management; Utilize continuous monitoring with Azure Security Center.

    Microsoft Azure Machine Learning Features:

    • Easy & flexible building interface: Execute your machine learning development through the Microsoft Azure Machine Learning Studio using drag-and-drop components that minimize the code development and straightforward configuration of properties. By being so flexible, the solution also helps build, test ,and generate advanced analytics based on the data.
    • Wide range of supported algorithms: Configuration is simple and easy because Microsoft Azure ML offers readily available well-known algorithms. There is also no limit in importing training data, and the solution enables you to fine-tune your data easily, saving money and time and helping you generate more revenue.
    • Easy implementation of web services: Simply drag and drop your data sets and algorithms, and link them together to implement web services. It only requires one click to create and publish the web service, which can be used from any device by passing valid credentials.
    • Great documentation: Microsoft Azure provides full stacks of documentation, such as tutorials, quick starts, references, and many other resources that help you understand how to easily build, manage, deploy, and access machine learning solutions effectively.

    Microsoft Azure Machine Learning Benefits:

    • It is fully integrated with Python and R SDKs.
    • It has an updated drag-and-drop interface, generally known as Azure Machine Learning Designer.
    • It supports MLPipelines, where you can build flexible and modular pipelines to automate workflows.
    • It supports multiple model formats depending upon the job type.
    • It has automated model training and hyperparameter tuning with code-first and no-code options.
    • It supports data labeling projects.

    Reviews from Real Users:

    "The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout.” - Channing S.l, Owner at Channing Stowell Associates

    "The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.” - Chris P., Tech Lead at a tech services company

    "The UI is very user-friendly and the AI is easy to use.” - Mikayil B., CRM Consultant at a computer software company

    "The solution is very fast and simple for a data science solution.” - Omar A., Big Data & Cloud Manager at a tech services company

    Offer
    Learn more about Databricks
    Learn more about Microsoft Azure Machine Learning Studio
    Sample Customers
    Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
    Walgreens Boots Alliance, Schneider Electric, BP
    Top Industries
    REVIEWERS
    Financial Services Firm15%
    Computer Software Company15%
    Mining And Metals Company15%
    Insurance Company8%
    VISITORS READING REVIEWS
    Computer Software Company27%
    Comms Service Provider15%
    Financial Services Firm8%
    Government5%
    REVIEWERS
    Financial Services Firm14%
    Recruiting/Hr Firm14%
    Computer Software Company14%
    Energy/Utilities Company14%
    VISITORS READING REVIEWS
    Computer Software Company24%
    Comms Service Provider19%
    Energy/Utilities Company6%
    Manufacturing Company6%
    Company Size
    REVIEWERS
    Small Business11%
    Midsize Enterprise18%
    Large Enterprise71%
    VISITORS READING REVIEWS
    Small Business25%
    Midsize Enterprise19%
    Large Enterprise56%
    REVIEWERS
    Small Business29%
    Midsize Enterprise14%
    Large Enterprise57%
    Find out what your peers are saying about Databricks vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: January 2022.
    563,327 professionals have used our research since 2012.

    Databricks is ranked 2nd in Data Science Platforms with 22 reviews while Microsoft Azure Machine Learning Studio is ranked 4th in Data Science Platforms with 16 reviews. Databricks is rated 7.8, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Databricks writes "Has a good feature set but it needs samples and templates to help invite users to see results". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Has the ability to do templating and transfer it so that we can do multiple types of models and data mining". Databricks is most compared with Amazon SageMaker, Azure Stream Analytics, Alteryx, Dataiku Data Science Studio and Google Cloud Datalab, whereas Microsoft Azure Machine Learning Studio is most compared with Dataiku Data Science Studio, IBM Watson Studio, KNIME, Alteryx and Amazon SageMaker. 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.