AWS Lambda is a serverless computing platform that lets users run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes of requirements to run and scale code with high availability.
$NaN
Per 1 ms
Google App Engine
Score 8.2 out of 10
N/A
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
React (React.js)
Score 8.8 out of 10
N/A
React or React.js is a JavaScript library for building user interfaces. React enables users to create interactive UIs.
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Pricing
AWS Lambda
Google App Engine
React (React.js)
Editions & Modules
128 MB
$0.0000000021
Per 1 ms
1024 MB
$0.0000000167
Per 1 ms
10240 MB
$0.0000001667
Per 1 ms
Starting Price
$0.05
Per Hour Per Instance
Max Price
$0.30
Per Hour Per Instance
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AWS Lambda
Google App Engine
React (React.js)
Free Trial
No
No
No
Free/Freemium Version
No
Yes
Yes
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
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AWS Lambda
Google App Engine
React (React.js)
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Chose AWS Lambda
AWS Lambda is good for short running functions, and ideally in response to events within AWS. Google App Engine is a more robust environment which can have complex code running for long periods of time, and across more than one instance of hardware. Google App Engine allows for …
For our organization, we selected Google App Engine which provides a reliable and efficient way to create and deploy apps moreover it supports a lot of languages and provides automatic debugging of code which enables us to deploy code to production as soon as development is …
If you have a small team which is also responsible for development of the product then surely go for it. And if you have a larger team with dedicated person to take care of deployments. Go for cheaper options such as compute engine or AWS (be sure to do your research on pricing …
You can create and scale Kubernetes clusters quickly, but you have to keep an eye on that cluster. In-App Engine, you don't have to worry about infrastructure, but in some scenarios, Kubernetes fits better.
Azure App Service is in par with Google App Engine although you may want to use Azure App Service if you are integrating with other Microsoft IT components, for example SQL Server. Google App Engine is great when in long run, you will be using Google cloud components, for …
The two giants are Google and Amazon. Both are very similar however Google App Engine allows you to deploy your web applications through platforms like Python where as if you're using AWS, you have full control on the operating system services. Google is good because you pay as …
I think that Microsoft and Amazon are simply investing more in their offerings, and there are a bunch of cool PaaS solutions out there as well. Google App Engine is solid, and is probably the right choice for some projects. But ultimately one should evaluate each platform …
Lambda excels at event-driven, short-lived tasks, such as processing files or building simple APIs. However, it's less ideal for long-running, computationally intensive, or applications that rely on carrying the state between jobs. Cold starts and constant load can easily balloon the costs.
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.
React is a JavaScript user interface construction library that works well for:
Developing web apps with dynamic and complicated user interfaces.
creating reusable UI elements that may be used in other applications.
creating single-page applications with dynamic content updates that don't require a page reload.
The Virtual DOM's effective updating mechanism allows it to handle large volumes of data updates.
React, on the other hand, might be less suitable for:
Websites that are simple, stagnant, and have no interaction. Other libraries or simple HTML, CSS, and JavaScript may be a better fit in such circumstances.
Web sockets may be a better choice for applications that need real-time updates, such as chat or gaming apps.
When creating mobile apps, React Native is a better option.
Server side rendering only, as React is designed to run on the client side.
React is fantastic for building performant user interfaces. Our web app is snappy and great for our customers.
React has the philosophy of doing one thing and doing it well which is the view layer of the application. This makes it incredibly intuitive and flexible for developers to use.
React has lead the way in being able to write modular and structured code. It is a drastic improvement since the days of spaghetti jQuery code.
React has an unmatched community. The amount of tools and libraries available is fantastic, and there plenty of solutions available online for common problems.
Developing test cases for Lambda functions can be difficult. For functions that require some sort of input it can be tough to develop the proper payload and event for a test.
For the uninitiated, deploying functions with Infrastructure as Code tools can be a challenging undertaking.
Logging the output of a function feels disjointed from running the function in the console. A tighter integration with operational logging would be appreciated, perhaps being able to view function logs from the Lambda console instead of having to navigate over to CloudWatch.
Sometimes its difficult to determine the correct permissions needed for Lambda execution from other AWS services.
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)
Debugging React is challenging. Bugs in react code generate stack traces internal to React and it is often totally unclear how it relates to the code you actually wrote.
Relating your React elements to corresponding DOM elements is difficult. The intentional separation of virtual and actual DOM also makes it difficult to map the elements to the structures in the DOM. This is partially ameliorated by the use of the React dev tool, which provides a DOM-like view of the React elements, but the tool still does not provide a direct correspondence with the DOM that is often necessary to figure out why something isn't right.
Because JSX is React-specific and not a language feature, a special compilation process is necessary to convert JSX code to normal JS. Coming from a C++ background, compiling things doesn't bother me, but many JS developers are used to a less structured development.
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.
I give it a seven is usability because it's AWS. Their UI's are always clunkier than the competition and their documentation is rather cumbersome. There's SO MUCH to dig through and it's a gamble if you actually end up finding the corresponding info if it will actually help. Like I said before, going to google with a specific problem is likely a better route because AWS is quite ubiquitous and chances are you're not the first to encounter the problem. That being said, using SAM (Serverless application model) and it's SAM Local environment makes running local instances of your Lambdas in dev environments painless and quite fun. Using Nodejs + Lambda + SAM Local + VS Code debugger = AWESOME.
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
React is just a bit of a different animal. I was avoiding it for the longest time. I thought for sure I would land on Vue or something else with a more approachable and familiar appearance. But after taking an online course in React, I started realize what people were raving about (and complaining about) and decided to implement it at our office for one of our products.
Amazon consistently provides comprehensive and easy-to-parse documentation of all AWS features and services. Most development team members find what they need with a quick internet search of the AWS documentation available online. If you need advanced support, though, you might need to engage an AWS engineer, and that could be an unexpected (or unwelcome) expense.
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.
Since it's open-source and very popular, the community support for React and related tools and libraries is excellent. There are a lot of people using the same tools, and so issues tend to get fixed quickly and "recipes" are easy to come by. And since it's backed by Facebook, they have a dedicated engineering team working on the progression of React.
AWS Lambda is good for short running functions, and ideally in response to events within AWS. Google App Engine is a more robust environment which can have complex code running for long periods of time, and across more than one instance of hardware. Google App Engine allows for both front-end and back-end infrastructure, while AWS Lambda is only for small back-end functions
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.
While this is a widely contested debate with various blog posts and benchmarks all over the place, its really a personal choice to determine what works for the team. Coming from a Angular 1.x background, I decided to try a new framework when Angular 2.x was announced and at that time React is gaining popularity and Vue hasn't taken off yet. Compared to Angular 1.x and Vue (hybrid of React and Angular) that split the logic from the html templates, I loved the way React breaks code into components using the jsx syntax. In my mind, this allows for cleaner components and easier maintenance
Positive - Only paying for when code is run, unlike virtual machines where you pay always regardless of processing power usage.
Positive - Scalability and accommodating larger amounts of demand is much cheaper. Instead of scaling up virtual machines and increasing the prices you pay for that, you are just increasing the number of times your lambda function is run.
Negative - Debugging/troubleshooting, and developing for lambda functions take a bit more time to get used to, and migrating code from virtual machines and normal processes to Lambda functions can take a bit of time.
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.