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Databricks Data Intelligence Platform vs. Google App Engine

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Databricks Data Intelligence Platform

    Score9 out of 10
    N/ADatabricks offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service provides a platform for data pipelines, data lakes, and data platforms.

    $0.07

    Per DBU

    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

    Pricing
    Databricks Data Intelligence PlatformGoogle App Engine
    Editions & Modules
    Standard
    $0.07
    Per DBU
    Premium
    $0.10
    Per DBU
    Enterprise
    $0.13
    Per DBU
    Starting Price
    $0.05
    Per Hour Per Instance
    Max Price
    $0.30
    Per Hour Per Instance
    Offerings
    Pricing Offerings
    Databricks Data Intelligence PlatformGoogle App Engine
    Free Trial
    NoNo
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Databricks Data Intelligence PlatformGoogle App Engine
    Considered Both Products
    Databricks
    No answer on this topic
    Google
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    16 Answers
    92%
    Would buy again
    12 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    16 Answers
    100%
    Delivers good value for the price
    13 Answers
    Happy with the feature set
    94%
    Happy with the feature set
    15 Answers
    92%
    Happy with the feature set
    12 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
    10 Answers
    Implementation went as expected
    92%
    Implementation went as expected
    12 Answers
    92%
    Implementation went as expected
    12 Answers
    Features
    Databricks Data Intelligence PlatformGoogle App Engine
    Platform-as-a-Service
    Comparison of Platform-as-a-Service features of Databricks Data Intelligence Platform and Google App Engine
    Feature
    Databricks Data Intelligence Platform
    -
    Ratings
    Google App Engine
    9.5
    32 Ratings
    20% above category average
    Ease of building user interfaces00 Ratings9.018 Ratings
    Scalability00 Ratings10.032 Ratings
    Platform management overhead00 Ratings9.032 Ratings
    Workflow engine capability00 Ratings8.024 Ratings
    Platform access control00 Ratings10.031 Ratings
    Services-enabled integration00 Ratings10.028 Ratings
    Development environment creation00 Ratings10.029 Ratings
    Development environment replication00 Ratings10.028 Ratings
    Issue monitoring and notification00 Ratings9.028 Ratings
    Issue recovery00 Ratings9.026 Ratings
    Upgrades and platform fixes00 Ratings10.029 Ratings
    Best Alternatives
    Databricks Data Intelligence PlatformGoogle App Engine
    Small Businesses
    No answers on this topic
    IBM Cloud Foundry
    Score8.5 out of 10
    Medium-sized Companies
    SAP Business Data Cloud
    Score8.6 out of 10
    IBM Cloud Private
    Score9.6 out of 10
    Enterprises
    SAP Business Data Cloud
    Score8.6 out of 10
    AWS Elastic Beanstalk
    Score8.6 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Databricks Data Intelligence PlatformGoogle App Engine
    Likelihood to Recommend
    9.4
    (21 ratings)
    9.0
    (36 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    8.3
    (8 ratings)
    Usability
    9.7
    (7 ratings)
    10.0
    (8 ratings)
    Performance
    -
    (0 ratings)
    10.0
    (1 ratings)
    Support Rating
    8.7
    (2 ratings)
    8.4
    (12 ratings)
    Implementation Rating
    -
    (0 ratings)
    8.0
    (1 ratings)
    Contract Terms and Pricing Model
    8.0
    (1 ratings)
    -
    (0 ratings)
    Professional Services
    10.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Databricks Data Intelligence PlatformGoogle App Engine
    Likelihood to Recommend
    Databricks
    Medium to Large data throughput shops will benefit the most from Databricks Spark processing. Smaller use cases may find the barrier to entry a bit too high for casual use cases. Some of the overhead to kicking off a Spark compute job can actually lead to your workloads taking longer, but past a certain point the performance returns cannot be beat.
    Incentivized
    Read full review
    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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    Pros
    Databricks
    • Process raw data in One Lake (S3) env to relational tables and views
    • Share notebooks with our business analysts so that they can use the queries and generate value out of the data
    • Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
    • Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers
    Incentivized
    Read full review
    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
    Cons
    Databricks
    • Sometimes, when multiple jobs depend on each other in different environments, it is not always easy to see the full workflow in one place.
    • It is sometimes difficult to determine which job or cluster contributes more to the overall cost.
    • For beginners, cluster configuration may be a little difficult. So more recommendation in the platform can help.
    Incentivized
    Read full review
    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
    Likelihood to Renew
    Databricks
    No answers on this topic
    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
    Usability
    Databricks
    Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

    in terms of graph generation and interaction it could improve their UI and UX
    Incentivized
    Read full review
    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
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    Support Rating
    Databricks
    One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
    Read full review
    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
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    Alternatives Considered
    Databricks
    The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when it comes to Spark Job Execution. Other platforms need to be self-managed, which is another huge hassle.
    Incentivized
    Read full review
    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
    Return on Investment
    Databricks
    • The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
    • DB has the ability to terminate/time out instances which helps manage cost.
    • The ability to quickly access typical hard to build data scenarios easily is a strength.
    Incentivized
    Read full review
    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
    ScreenShots