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Azure Machine Learning vs. IBM Watson Studio on Cloud Pak for Data

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Azure Machine Learning

    Score8.2 out of 10
    N/AMicrosoft's Azure Machine Learning is and end-to-end data science and analytics solution that helps professional data scientists to prepare data, develop experiments, and deploy models in the cloud. It replaces the Azure Machine Learning Workbench.

    $0

    per month

    IBM Watson Studio

    Score10 out of 10
    N/AIBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI lifecycle management and accelerates time to value with an open, flexible multicloud architecture.N/A
    Pricing
    Azure Machine LearningIBM Watson Studio
    Editions & Modules
    Studio Pricing - Free
    $0.00
    per month
    Production Web API - Dev/Test
    $0.00
    per month
    Studio Pricing - Standard
    $9.99
    per ML studio workspace/per month
    Production Web API - Standard S1
    $100.13
    per month
    Production Web API - Standard S2
    $1000.06
    per month
    Production Web API - Standard S3
    $9999.98
    per month
    No answers on this topic
    Offerings
    Pricing Offerings
    Azure Machine LearningIBM Watson Studio
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Azure Machine LearningIBM Watson Studio
    Considered Both Products
    Microsoft
    Chose Azure Machine Learning
    The Azure Machine Learning Studio eliminates the complex tasks of data engineering and python coding for the data scientists to build models a simpler way. While SageMaker provide[s] a similar environment, [it] requires higher knowledge of data engineering. Even same for the …
    Incentivized
    IBM
    Chose IBM Watson Studio
    The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and …
    Incentivized
    Chose IBM Watson Studio
    Watson Studio offers more capabilities and diversity in tools and services.
    Incentivized
    Chose IBM Watson Studio
    DSX is a good challenger for Databricks and co. It is Enterprise ready and well integrated.
    Incentivized
    Chose IBM Watson Studio
    I wanted an environment that can support multiple users without any restrictions. Also, R-Studio does not provide a collaborative environment for multiple users. The Auto feature selection in the SPSS modeler is a good node in DSx which helps make statistical decisions on …
    Incentivized
    Chose IBM Watson Studio
    Although we also use Azure ML services we prefer DSX because of SPSS integration.
    Incentivized
    Key User Insights
    Would buy again
    No answers on this topic
    No answers on this topic
    Delivers good value for the price
    No answers on this topic
    No answers on this topic
    Happy with the feature set
    No answers on this topic
    No answers on this topic
    Lived up to sales and marketing promises
    No answers on this topic
    No answers on this topic
    Implementation went as expected
    No answers on this topic
    No answers on this topic
    Features
    Azure Machine LearningIBM Watson Studio
    Platform Connectivity
    Comparison of Platform Connectivity features of Azure Machine Learning and IBM Watson Studio on Cloud Pak for Data
    Feature
    Azure Machine Learning
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    8.1
    22 Ratings
    Connect to Multiple Data Sources00 Ratings8.022 Ratings
    Extend Existing Data Sources00 Ratings8.022 Ratings
    Automatic Data Format Detection00 Ratings10.021 Ratings
    MDM Integration00 Ratings6.414 Ratings
    Data Exploration
    Comparison of Data Exploration features of Azure Machine Learning and IBM Watson Studio on Cloud Pak for Data
    Feature
    Azure Machine Learning
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    10.0
    22 Ratings
    Visualization00 Ratings10.022 Ratings
    Interactive Data Analysis00 Ratings10.022 Ratings
    Data Preparation
    Comparison of Data Preparation features of Azure Machine Learning and IBM Watson Studio on Cloud Pak for Data
    Feature
    Azure Machine Learning
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    Interactive Data Cleaning and Enrichment00 Ratings10.022 Ratings
    Data Transformations00 Ratings10.021 Ratings
    Data Encryption00 Ratings8.020 Ratings
    Built-in Processors00 Ratings10.021 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of Azure Machine Learning and IBM Watson Studio on Cloud Pak for Data
    Feature
    Azure Machine Learning
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    Multiple Model Development Languages and Tools00 Ratings10.021 Ratings
    Automated Machine Learning00 Ratings10.022 Ratings
    Single platform for multiple model development00 Ratings10.022 Ratings
    Self-Service Model Delivery00 Ratings8.020 Ratings
    Model Deployment
    Comparison of Model Deployment features of Azure Machine Learning and IBM Watson Studio on Cloud Pak for Data
    Feature
    Azure Machine Learning
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    8.0
    22 Ratings
    Flexible Model Publishing Options00 Ratings9.022 Ratings
    Security, Governance, and Cost Controls00 Ratings7.022 Ratings
    User Ratings
    Azure Machine LearningIBM Watson Studio
    Likelihood to Recommend
    8.0
    (4 ratings)
    8.0
    (65 ratings)
    Likelihood to Renew
    7.0
    (1 ratings)
    8.2
    (1 ratings)
    Usability
    7.0
    (2 ratings)
    9.6
    (2 ratings)
    Availability
    -
    (0 ratings)
    8.2
    (1 ratings)
    Performance
    -
    (0 ratings)
    8.2
    (1 ratings)
    Support Rating
    7.9
    (2 ratings)
    8.2
    (1 ratings)
    In-Person Training
    -
    (0 ratings)
    8.2
    (1 ratings)
    Online Training
    -
    (0 ratings)
    8.2
    (1 ratings)
    Implementation Rating
    8.0
    (1 ratings)
    7.3
    (1 ratings)
    Product Scalability
    -
    (0 ratings)
    8.2
    (1 ratings)
    Vendor post-sale
    -
    (0 ratings)
    7.3
    (1 ratings)
    Vendor pre-sale
    -
    (0 ratings)
    8.2
    (1 ratings)