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Google Cloud AI vs. IBM Watson Studio on Cloud Pak for Data

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Google Cloud AI

    Score8.7 out of 10
    N/AGoogle Cloud AI provides modern machine learning services, with pre-trained models and a service to generate tailored models.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
    Google Cloud AIIBM Watson Studio
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Google Cloud AIIBM 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
    Google Cloud AIIBM Watson Studio
    Considered Both Products
    Google
    No answer on this topic
    IBM
    Chose IBM Watson Studio
    DSX performed almost 2.5 times faster than Microsoft's free Jupyter Notebook service on their Azure platform.
    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
    Google Cloud AIIBM Watson Studio
    Platform Connectivity
    Comparison of Platform Connectivity features of Google Cloud AI and IBM Watson Studio on Cloud Pak for Data
    Feature
    Google Cloud AI
    -
    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 Google Cloud AI and IBM Watson Studio on Cloud Pak for Data
    Feature
    Google Cloud AI
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    10.0
    22 Ratings
    17% above category average
    Visualization00 Ratings10.022 Ratings
    Interactive Data Analysis00 Ratings10.022 Ratings
    Data Preparation
    Comparison of Data Preparation features of Google Cloud AI and IBM Watson Studio on Cloud Pak for Data
    Feature
    Google Cloud AI
    -
    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 Google Cloud AI and IBM Watson Studio on Cloud Pak for Data
    Feature
    Google Cloud AI
    -
    Ratings
    IBM Watson Studio on Cloud Pak for Data
    9.5
    22 Ratings
    12% 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 Google Cloud AI and IBM Watson Studio on Cloud Pak for Data
    Feature
    Google Cloud AI
    -
    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
    Best Alternatives
    Google Cloud AIIBM Watson Studio
    Small Businesses
    TensorFlow
    Score7.6 out of 10
    RapidMiner
    Score8.9 out of 10
    Medium-sized Companies
    TensorFlow
    Score7.6 out of 10
    Anaconda
    Score8.8 out of 10
    Enterprises
    TensorFlow
    Score7.6 out of 10
    Posit
    Score10 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google Cloud AIIBM Watson Studio
    Likelihood to Recommend
    8.0
    (7 ratings)
    8.0
    (65 ratings)
    Likelihood to Renew
    10.0
    (1 ratings)
    8.2
    (1 ratings)
    Usability
    8.0
    (2 ratings)
    9.6
    (2 ratings)
    Availability
    -
    (0 ratings)
    8.2
    (1 ratings)
    Performance
    -
    (0 ratings)
    8.2
    (1 ratings)
    Support Rating
    7.3
    (3 ratings)
    8.2
    (1 ratings)
    In-Person Training
    -
    (0 ratings)
    8.2
    (1 ratings)
    Online Training
    -
    (0 ratings)
    8.2
    (1 ratings)
    Implementation Rating
    10.0
    (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)
    User Testimonials
    Google Cloud AIIBM Watson Studio
    Likelihood to Recommend
    Google
    Google Cloud AI is a wonderful product for companies that are looking to offset AI and ML processing power to cloud APIs, and specific Machine Learning use cases to APIs as well. For companies that are looking for very specific, customized ML capabilities that require lots of fine-tuning, it may be better to do this sort of processing through open-source libraries locally, to offset the costs that your company might incur through this API usage.
    Incentivized
    Read full review
    IBM
    It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.
    Incentivized
    Read full review
    Pros
    Google
    • good conversion from the voice to the text
    • speed in the conversion from voice to text
    • time-saving in the conversion activity
    • analysis of the results of the conversion in real time
    Incentivized
    Read full review
    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
    Google
    • Some of the build in/supported AI modules that can be deployed, for example Tensorflow, do not have up-to-date documentation so what is actually implemented in the latest rev is not what is mentioned in the documentation, resulting in a lot of debugging time.
    • Customization of existing modules and libraries is harder and it does need time and experience to learn.
    • Google Cloud AI can do a better job in providing better support for Python and other coding languages.
    Incentivized
    Read full review
    IBM
    • The cost is steep and so only companies with resources can afford it
    • It will be nice to have Chinese versions so that Chinese engineers can also use it easily
    • It takes a while to learn how to input different kinds of skin defects for detection
    Incentivized
    Read full review
    Likelihood to Renew
    Google
    We are extremely satisfied with the impact that this tool has made on our organization since we have practically moved from crawling to walking in the process of generating information for our main task to investigate in the field through interviews. With the audio to text translation tool there is a difference from heaven to earth in the time of feeding our internal data.
    Incentivized
    Read full review
    IBM
    because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)
    Incentivized
    Read full review
    Usability
    Google
    I give 8 because although it´s a tool I really enjoy working with, I think Google Cloud AI's impact is just starting, therefore I can visualize a lot/space of improvements in this tool. As an example the application of AI in international environments with different languages is a good example of that space/room to improve.
    Read full review
    IBM
    The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
    Incentivized
    Read full review
    Reliability and Availability
    Google
    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
    Google
    No answers on this topic
    IBM
    Never had slow response even on our very busy network
    Incentivized
    Read full review
    Support Rating
    Google
    Every rep has been nice and helpful whenever I call for help. One of the systems froze and wouldn't start back up and with the help of our assigned rep we got everything back up in a timely manner. This helped us not lose customers and money.
    Incentivized
    Read full review
    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
    Google
    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
    Google
    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
    Google
    In fact, you only need the basic tech knowledge to do a Google search. You need to know if your organization requires it or not,. our organization required it. And that is why we acquired it and solved a need that we had been suffering from. This is part of the modernization of an organization and part of its growth as a company.
    Incentivized
    Read full review
    IBM
    It surprised us with unpredictable case of use and brand new points of view
    Incentivized
    Read full review
    Alternatives Considered
    Google
    These are basic tools although useful, you can't simply ignore them or say they are not good. These tools also have their own values. But, Yes, Google is an advanced one, A king in the field of offering a wide range of tools, quality, speed, easy to use, automation, prebuild, and cost-effective make them a leader and differentiate them from others.
    Incentivized
    Read full review
    IBM
    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 does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.
    Incentivized
    Read full review
    Scalability
    Google
    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
    Google
    • Artificial intelligence and automation seems 'free' and draws the organization in, without seeming to spend a lot of funds. A positive impact, but who is actually tracking the cost?
    • We want our employees to use it, but many resist technology or are scared of it, so we need a way to make them feel more comfortable with the AI.
    • The ROI seems positive since we are full in with Google, and the tools come along with the functionality.
    Incentivized
    Read full review
    IBM
    • Could instantly show data driven insights to drive 20% incremental revenue over existing results
    • Still don't have a real use case for unstructured data like twitter feed
    • Some of the insights around user actions have driven new projects to automate mundane tasks
    Incentivized
    Read full review
    ScreenShots