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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Google App Engine

    Score8.4 out of 10
    N/AGoogle App Engine is Google Cloud's platform-as-a-service offering. It features pay-per-use pricing and support for a broad array of programming languages.

    $0.05

    Per Hour Per Instance

    IBM Cloud Pak for Data

    Score7.4 out of 10
    N/AIBM Cloud Pak for Data (formerly IBM Cloud Private for Data) provides data management, data governance, and automated data discovery and classification.N/A
    Pricing
    Google App EngineIBM Cloud Pak for Data
    Editions & Modules
    Starting Price
    $0.05
    Per Hour Per Instance
    Max Price
    $0.30
    Per Hour Per Instance
    No answers on this topic
    Offerings
    Pricing Offerings
    Google App EngineIBM Cloud Pak for Data
    Free Trial
    NoNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Google App EngineIBM Cloud Pak for Data
    Considered Both Products
    Google
    No answer on this topic
    IBM
    No answer on this topic
    Key User Insights
    Would buy again
    92%
    Would buy again
    12 Answers
    100%
    Would buy again
    9 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    13 Answers
    100%
    Delivers good value for the price
    9 Answers
    Happy with the feature set
    92%
    Happy with the feature set
    12 Answers
    100%
    Happy with the feature set
    9 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    10 Answers
    100%
    Lived up to sales and marketing promises
    6 Answers
    Implementation went as expected
    92%
    Implementation went as expected
    12 Answers
    100%
    Implementation went as expected
    7 Answers
    Features
    Google App EngineIBM Cloud Pak for Data
    Platform-as-a-Service
    Comparison of Platform-as-a-Service features of Google App Engine and IBM Cloud Pak for Data
    Feature
    Google App Engine
    9.5
    32 Ratings
    20% above category average
    IBM Cloud Pak for Data
    -
    Ratings
    Ease of building user interfaces9.018 Ratings00 Ratings
    Scalability10.032 Ratings00 Ratings
    Platform management overhead9.032 Ratings00 Ratings
    Workflow engine capability8.024 Ratings00 Ratings
    Platform access control10.031 Ratings00 Ratings
    Services-enabled integration10.028 Ratings00 Ratings
    Development environment creation10.029 Ratings00 Ratings
    Development environment replication10.028 Ratings00 Ratings
    Issue monitoring and notification9.028 Ratings00 Ratings
    Issue recovery9.026 Ratings00 Ratings
    Upgrades and platform fixes10.029 Ratings00 Ratings
    Best Alternatives
    Google App EngineIBM Cloud Pak for Data
    Small Businesses
    IBM Cloud Foundry
    Score8.5 out of 10
    No answers on this topic
    Medium-sized Companies
    IBM Cloud Private
    Score9.6 out of 10
    No answers on this topic
    Enterprises
    AWS Elastic Beanstalk
    Score8.6 out of 10
    No answers on this topic
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google App EngineIBM Cloud Pak for Data
    Likelihood to Recommend
    9.0
    (36 ratings)
    8.9
    (9 ratings)
    Likelihood to Renew
    8.3
    (8 ratings)
    9.1
    (2 ratings)
    Usability
    10.0
    (8 ratings)
    -
    (0 ratings)
    Performance
    10.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    8.4
    (12 ratings)
    -
    (0 ratings)
    Implementation Rating
    8.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Google App EngineIBM Cloud Pak for Data
    Likelihood to Recommend
    Google
    App Engine is such a good resource for our team both internally and externally. You have complete control over your app, how it runs, when it runs, and more while Google handles the back-end, scaling, orchestration, and so on. If you are serving a tool, system, or web page, it's perfect. If you are serving something back-end, like an automation or ETL workflow, you should be a little considerate or careful with how you are structuring that job. For instance, the Standard environment in Google App Engine will present you with a resource limit for your server calls. If your operations are known to take longer than, say, 10 minutes or so, you may be better off moving to the Flexible environment (which may be a little more expensive but certainly a little more powerful and a little less limited) or even moving that workflow to something like Google Compute Engine or another managed service.
    Incentivized
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    IBM
    IBM Cloud Pak for Data with Netezza is well suited for clients who require fast, economical analytics processing. It is not designed to be used as a transactional processing environment. For example, a large customer is using it during the point of sale process. That makes little sense in that business case. However, to take analysis to market faster, it excels well in that space.
    Incentivized
    Read full review
    Pros
    Google
    • Quick to develop, quick to deploy. You can be up and running on Google App Engine in no time.
    • Flexible. We use Java for some services and Node.js for others.
    • Great security features. We have been consistently impressed with the security and authentication features of Google App Engine.
    Incentivized
    Read full review
    IBM
    • Increases our impact by combining BI skills with advanced analytics and machine learning in an easy to use visual interface.
    • Visualization and reporting.
    • Rapidly provides business -ready data to all users equally.
    • Manage data spread across distributed stores and clouds.
    Incentivized
    Read full review
    Cons
    Google
    • There is a slight learning curve to getting used to code on Google App Engine.
    • Google Cloud Datastore is Google's NoSQL database in the cloud that your applications can use. NoSQL databases, by design, cannot give handle complex queries on the data. This means that sometimes you need to think carefully about your data structures - so that you can get the results you need in your code.
    • Setting up billing is a little annoying. It does not seem to save billing information to your account so you can re-use the same information across different Cloud projects. Each project requires you to re-enter all your billing information (if required)
    Incentivized
    Read full review
    IBM
    • Cannot save changes to some secrets in the internal vault
    • Sign-in issues on environments where IAM is enabled
    • The Enforce quotas option is disabled
    Incentivized
    Read full review
    Likelihood to Renew
    Google
    App Engine is a solid choice for deployments to Google Cloud Platform that do not want to move entirely to a Kubernetes-based container architecture using a different Google product. For rapid prototyping of new applications and fairly straightforward web application deployments, we'll continue to leverage the capabilities that App Engine affords us.
    Incentivized
    Read full review
    IBM
    No answers on this topic
    Usability
    Google
    I had to revisit the UI after a year of just setting up and forgetting. The UI got some improvements but the amount of navigation we have to go through to setup a new app has increased but also got easier to setup. Gemini now is integrated and make getting answers faster
    Incentivized
    Read full review
    IBM
    No answers on this topic
    Support Rating
    Google
    Good amount of documentation available for Google App Engine and in general there is large developer community around Google App Engine and other products it interacts with. Lastly, Google support is great in general. No issues so far with them.
    Incentivized
    Read full review
    IBM
    No answers on this topic
    Alternatives Considered
    Google
    We were on another much smaller cloud provider and decided to make the switch for several reasons - stability, breadth of services, and security. In reviewing options, GCP provided the best mixtures of meeting our needs while also balancing the overall cost of the service as compared to the other major players in Azure and AWS.
    Incentivized
    Read full review
    IBM
    IBM Cloud Pak for Data takes the IBM Cognos solution and provides this on an enterprise cloud platform that can be extended to support better data integration and data science capabilities.
    Incentivized
    Read full review
    Return on Investment
    Google
    • Effective employee adoption through ease of use.
    • Effective integration to other java based frameworks.
    • Time to market is very quick. Build, test, deploy and use.
    • The GAE Whitelist for java is an important resource to know what works and what does not. So use it. It would also be nice for Google to expand on items that are allowed on GAE platform.
    Incentivized
    Read full review
    IBM
    • We have the ability to access all our data much quicker through the unified search option.
    • 30% increase in productivity through the introduction of AI.
    • Improved data security and governance.
    Incentivized
    Read full review
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