Google 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
Microsoft Power BI
Score 8.5 out of 10
N/A
Microsoft Power BI is a visualization and data discovery tool from Microsoft. It allows users to convert data into visuals and graphics, visually explore and analyze data, collaborate on interactive dashboards and reports, and scale across their organization with built-in governance and security.
$168
per year per user
Pricing
Google App Engine
Microsoft Power BI
Editions & Modules
Starting Price
$0.05
Per Hour Per Instance
Max Price
$0.30
Per Hour Per Instance
Power BI Pro
$14
per month (billed annually) per user
Power BI Premium
$24
per month (billed annually) per user
Offerings
Pricing Offerings
Google App Engine
Microsoft Power BI
Free Trial
No
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
Power BI Desktop is the data exploration and report authoring experience for Power BI, and is available as a free download.
More Pricing Information
Community Pulse
Google App Engine
Microsoft Power BI
Features
Google App Engine
Microsoft Power BI
Platform-as-a-Service
Comparison of Platform-as-a-Service features of Product A and Product B
Google App Engine
9.5
32 Ratings
20% above category average
Microsoft Power BI
-
Ratings
Ease of building user interfaces
9.018 Ratings
00 Ratings
Scalability
10.032 Ratings
00 Ratings
Platform management overhead
9.032 Ratings
00 Ratings
Workflow engine capability
8.024 Ratings
00 Ratings
Platform access control
10.031 Ratings
00 Ratings
Services-enabled integration
10.028 Ratings
00 Ratings
Development environment creation
10.029 Ratings
00 Ratings
Development environment replication
10.028 Ratings
00 Ratings
Issue monitoring and notification
9.028 Ratings
00 Ratings
Issue recovery
9.026 Ratings
00 Ratings
Upgrades and platform fixes
10.029 Ratings
00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Google App Engine
-
Ratings
Microsoft Power BI
8.2
198 Ratings
0% above category average
Pixel Perfect reports
00 Ratings
8.2169 Ratings
Customizable dashboards
00 Ratings
8.7197 Ratings
Report Formatting Templates
00 Ratings
7.8180 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Google App Engine
-
Ratings
Microsoft Power BI
7.9
196 Ratings
2% below category average
Drill-down analysis
00 Ratings
8.3193 Ratings
Formatting capabilities
00 Ratings
7.7193 Ratings
Integration with R or other statistical packages
00 Ratings
7.4143 Ratings
Report sharing and collaboration
00 Ratings
8.3191 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Google App Engine
-
Ratings
Microsoft Power BI
8.0
189 Ratings
3% below category average
Publish to Web
00 Ratings
8.1179 Ratings
Publish to PDF
00 Ratings
7.9174 Ratings
Report Versioning
00 Ratings
7.7145 Ratings
Report Delivery Scheduling
00 Ratings
8.3148 Ratings
Delivery to Remote Servers
00 Ratings
7.9111 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
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.
Has significantly improved collation of data and visualisation especially with business across Europe. Has given me the ability to see the Site availability at the click of a button to see which Site is in the "money" and seize opportunities based on Market data
Options for data source connections are immense. Not just which sources, but your options for *how* the data is brought in.
Constant updates (this is both good and bad at times).
User friendliness. I can get the data connections set up and draft some quick visuals, then release to the target audience and let them expand on it how they want to.
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)
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.
Microsoft Power BI is an excellent and scalable tool. It has a learning curve, but once you get past that, the sky is the limit and you can build from the most simple to the most complex dashboards. I have built everything from simple reports with only a few data points to complex reports with many pages and advanced filtering.
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
Automating reporting has reduced manual data processing by 50-70%, freeing up analysts for higher-value tasks. A finance team that previously spent 20+ hours per week on Excel-based reports now does it in minutes with Microsoft Power BI's automated Real-time dashboards have shortened decision cycles by 30-40%, enabling leadership to react quickly to sales trends, operational bottlenecks, and customer behavior.
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.
It is a fantastic tool, you can do almost everything related with data and reports, it is a perfect substitutive of Power Point and Excel with a high evolution and flexibility, and also it is very friendly and easy to share. I think all companies should have Power BI (or other BI tool) in their software package and if they are in the MS Suite, for sure Power BI should be the one due to all the benefits of the MS ecosystem.
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.
Microsoft Power BI is free. If I didn't want to create a custom platform (i.e. my organization insisted on an existing platform that I *had* to use), I'd use Microsoft Power BI. For any start-up or SMB, I'd just use Claude & Grok to build it quickly, also for free. Would not pay for Tableau or Sigma anymore. Not worth it at all.
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.