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Amazon SageMaker vs. IBM Watson Studio on Cloud Pak for Data

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Amazon SageMaker

    Score8.2 out of 10
    N/AAmazon SageMaker enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.N/A

    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
    Amazon SageMakerIBM Watson Studio
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Amazon SageMakerIBM 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
    Amazon SageMakerIBM Watson Studio
    Considered Both Products
    Amazon AWS
    Chose Amazon SageMaker
    Amazon SageMaker comes with other supportive services like S3, SQS, and a vast variety of servers on EC2. It's very comfortable to manage the process and also support the end application by one click hosting option. Also, it charges on the base of what you use and how long you …
    Incentivized
    IBM
    Chose IBM Watson Studio
    Not applicable
    Incentivized
    Key User Insights
    Would buy again
    No answers on this topic
    100%
    Would buy again
    5 Answers
    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
    100%
    Happy with the feature set
    5 Answers
    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
    Amazon SageMakerIBM Watson Studio
    Platform Connectivity
    Comparison of Platform Connectivity features of Amazon SageMaker and IBM Watson Studio on Cloud Pak for Data
    Feature
    Amazon SageMaker
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    8.1
    22 Ratings
    3% below category average
    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 Amazon SageMaker and IBM Watson Studio on Cloud Pak for Data
    Feature
    Amazon SageMaker
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    10.0
    22 Ratings
    18% above category average
    Visualization00 Ratings10.022 Ratings
    Interactive Data Analysis00 Ratings10.022 Ratings
    Data Preparation
    Comparison of Data Preparation features of Amazon SageMaker and IBM Watson Studio on Cloud Pak for Data
    Feature
    Amazon SageMaker
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    15% above category average
    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 Amazon SageMaker and IBM Watson Studio on Cloud Pak for Data
    Feature
    Amazon SageMaker
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    13% above category average
    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 Amazon SageMaker and IBM Watson Studio on Cloud Pak for Data
    Feature
    Amazon SageMaker
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    8.0
    22 Ratings
    6% below category average
    Flexible Model Publishing Options00 Ratings9.022 Ratings
    Security, Governance, and Cost Controls00 Ratings7.022 Ratings
    User Ratings
    Amazon SageMakerIBM Watson Studio
    Likelihood to Recommend
    9.0
    (5 ratings)
    8.0
    (65 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    8.2
    (1 ratings)
    Usability
    -
    (0 ratings)
    9.6
    (2 ratings)
    Availability
    -
    (0 ratings)
    8.2
    (1 ratings)
    Performance
    -
    (0 ratings)
    8.2
    (1 ratings)
    Support Rating
    -
    (0 ratings)
    8.2
    (1 ratings)
    In-Person Training
    -
    (0 ratings)
    8.2
    (1 ratings)
    Online Training
    -
    (0 ratings)
    8.2
    (1 ratings)
    Implementation Rating
    -
    (0 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)
    User Testimonials
    Amazon SageMakerIBM Watson Studio
    Likelihood to Recommend
    Amazon AWS
    No answers on this topic
    IBM
    No answers on this topic
    Pros
    Amazon AWS
    No answers on this topic
    IBM
    • Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc.
    • SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly.
    • Enforced best-practices set up POCs for deployment in production with a minimum of re-work.
    • Estimator validation lets data scientists test and prove different models.
    Incentivized
    Read full review
    Cons
    Amazon AWS
    No answers on this topic
    IBM
    No answers on this topic
    Likelihood to Renew
    Amazon AWS
    No answers on this topic
    IBM
    because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)
    Incentivized
    Read full review
    Usability
    Amazon AWS
    No answers on this topic
    IBM
    The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
    Incentivized
    Read full review
    Reliability and Availability
    Amazon AWS
    No answers on this topic
    IBM
    From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected
    Incentivized
    Read full review
    Performance
    Amazon AWS
    No answers on this topic
    IBM
    Never had slow response even on our very busy network
    Incentivized
    Read full review
    Support Rating
    Amazon AWS
    No answers on this topic
    IBM
    I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path
    Incentivized
    Read full review
    In-Person Training
    Amazon AWS
    No answers on this topic
    IBM
    The trainers on the job are very smart with solutions and very able in teaching
    Incentivized
    Read full review
    Online Training
    Amazon AWS
    No answers on this topic
    IBM
    The Platform is very handy and suggests further steps according my previous interests
    Incentivized
    Read full review
    Implementation Rating
    Amazon AWS
    No answers on this topic
    IBM
    It surprised us with unpredictable case of use and brand new points of view
    Incentivized
    Read full review
    Alternatives Considered
    Amazon AWS
    No answers on this topic
    IBM
    No answers on this topic
    Scalability
    Amazon AWS
    No answers on this topic
    IBM
    It helped us in getting from 0 to DSX without getting lost
    Incentivized
    Read full review
    Return on Investment
    Amazon AWS
    • We have been able to deliver data products more rapidly because we spend less time building data pipelines and model servers.
    • We can prototype more rapidly because it is easy to configure notebooks to access AWS resources.
    • For our use-cases, serving models is less expensive with SageMaker than bespoke servers.
    Incentivized
    Read full review
    IBM
    No answers on this topic
    ScreenShots