Anaconda vs Microsoft Azure Machine Learning Studio comparison

Cancel
You must select at least 2 products to compare!
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Anaconda and Microsoft Azure Machine Learning Studio based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms.
To learn more, read our detailed Data Science Platforms Report (Updated: March 2024).
763,955 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The most valuable feature is the Jupyter notebook that allows us to write the Python code, compile it on the fly, and then look at the results.""I can use Anaconda for non-heavy tasks.""It helped us find find the optimal area for where our warehouse should be located.""The most advantageous feature is the logic building.""The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code.""The notebook feature is an improvement over RStudio.""The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly.""With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager, "Conda", makes life easy when it comes to managing and installing packages."

More Anaconda Pros →

"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 solution is very fast and simple for a data science solution.""It's good for citizen data scientists, but also, other people can use Python or .NET code.""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.""When you import the dataset you can see the data distribution easily with graphics and statistical measures.""The UI is very user-friendly and that AI is easy to use.""Their web interface is good.""The interface is very intuitive."

More Microsoft Azure Machine Learning Studio Pros →

Cons
"One thing that hurts the product is that the company is not doing more to advertise it as a solution and make it more well known.""It crashes once in a while. In case of a reboot or something unexpected, the unseen code part will get diminished, and it relatively takes longer than other applications when a reboot is happening. They can improve in these areas. They can also bring some database software. They have software for analytics and virtualization. However, they don't have any software for the database.""The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform.""The interface could be improved. Other solutions, like Visual Studio, have much better UI.""One feature that I would like to see is being able to use a different language in a different cell, which would allow me to mix R and Python together.""I think that the framework can be improved to make it easier for people to discover and use things on their own.""Anaconda should be optimized for RAM consumption.""Having a small guide or video on the tool would help learn how to use it and what the features are."

More Anaconda Cons →

"There should be data access security, a role level security. Right now, they don't offer this.""The data cleaning functionality is something that could be better and needs to be improved.""Microsoft should also include more examples and tutorials for using this product.​""This solution could be improved if they could integrate the data pipeline scheduling part for their interface.""Microsoft Azure Machine Learning Studio worked okay for me, so right now, I don't have any room for improvement in mind for it. What I'd like added to Microsoft Azure Machine Learning Studio in its next version is a categorization for use cases or a template that makes the use cases simple to map out, for example, for healthcare, medical, or finance use cases, etc. This would be very helpful for users of Microsoft Azure Machine Learning Studio, especially for beginners.""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.""I would like to see modules to handle Deep Learning frameworks.""Stability-wise, you may face certain problems when you fail to refresh the data in the solution."

More Microsoft Azure Machine Learning Studio Cons →

Pricing and Cost Advice
  • "The licensing costs for Anaconda are reasonable."
  • "The product is open-source and free to use."
  • "My company uses the free version of the tool. There is also a paid version of the tool available."
  • More Anaconda Pricing and Cost Advice →

  • "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."
  • "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."
  • "From a developer's perspective, I find the price of this solution high."
  • "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."
  • "In terms of pricing, for any cloud solution, you should know the tricks of the trade and how to use it, otherwise, you'll end up paying a lot of money irrespective of the cloud provider, so at least for Microsoft Azure Machine Learning Studio pricing versus AWS, I would rate it three out of five, with one being the most expensive, and five being the cheapest. It could be cheaper, but you also have to be careful when choosing the plans, for example, consider the architecture and a lot of other factors before choosing your plan, if you don't want to end up paying more. If your cloud provider has an optimizer that seems to be available in every provider, that would keep alerting you in terms of resources not being used as much, then that would help you with budgeting."
  • "My team didn't deal with the licensing for Microsoft Azure Machine Learning Studio, so I'm unable to comment on pricing, but the money that was spent on the tool was worth it."
  • More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →

    report
    Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
    763,955 professionals have used our research since 2012.
    Questions from the Community
    Top Answer:Pricing is a matter of open source versus proprietary. Anaconda is open source and openly publishes their pricing models. RapidMiner is proprietary and you must receive a quote depending on your use… more »
    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 »
    Ranking
    18th
    Views
    2,965
    Comparisons
    2,207
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    2nd
    Views
    15,820
    Comparisons
    12,975
    Reviews
    23
    Average Words per Review
    494
    Rating
    7.6
    Comparisons
    Also Known As
    Azure Machine Learning, MS Azure Machine Learning Studio
    Learn More
    Overview

    Anaconda makes it easy for you to install and maintain Python environments. Our development team tests to ensure compatibility of Python packages in Anaconda. We support and provide open source assurance for packages in Anaconda to mitigate your risk in using open source and meet your regulatory compliance requirements.

    Python is the fastest growing language for data science. Anaconda includes 720+ Python open source packages and now includes essential R packages. This powerful combination allows you to do everything you want from BI to advanced modeling on complex Big Data

    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

    Sample Customers
    LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone
    Walgreens Boots Alliance, Schneider Electric, BP
    Top Industries
    REVIEWERS
    Financial Services Firm27%
    Manufacturing Company18%
    Energy/Utilities Company9%
    Computer Software Company9%
    VISITORS READING REVIEWS
    Financial Services Firm17%
    Computer Software Company11%
    Government10%
    Manufacturing Company6%
    REVIEWERS
    Financial Services Firm17%
    Energy/Utilities Company13%
    Comms Service Provider9%
    Retailer9%
    VISITORS READING REVIEWS
    Financial Services Firm12%
    Computer Software Company11%
    Manufacturing Company8%
    Healthcare Company7%
    Company Size
    REVIEWERS
    Small Business41%
    Large Enterprise59%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise13%
    Large Enterprise69%
    REVIEWERS
    Small Business31%
    Midsize Enterprise9%
    Large Enterprise60%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise11%
    Large Enterprise72%
    Buyer's Guide
    Data Science Platforms
    March 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: March 2024.
    763,955 professionals have used our research since 2012.

    Anaconda is ranked 18th in Data Science Platforms with 1 review while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 22 reviews. Anaconda is rated 7.8, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Anaconda writes "Offers free version and is helpful to handle small-scale workloads". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Has a drag and drop feature and easier learning curve, but the number of algorithms available could still be improved". Anaconda is most compared with Databricks, Amazon SageMaker, Microsoft Power BI, IBM SPSS Statistics and Domino Data Science Platform, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, Azure OpenAI, TensorFlow and SAS Visual Analytics.

    See our list of best Data Science Platforms vendors.

    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.