AWS Lambda vs Google App Engine: What are the differences?
What is AWS Lambda? Automatically run code in response to modifications to objects in Amazon S3 buckets, messages in Kinesis streams, or updates in DynamoDB. AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.
What is Google App Engine? Build web applications on the same scalable systems that power Google applications. Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.
AWS Lambda can be classified as a tool in the "Serverless / Task Processing" category, while Google App Engine is grouped under "Platform as a Service".
Some of the features offered by AWS Lambda are:
- Extend other AWS services with custom logic
- Build custom back-end services
- Completely Automated Administration
On the other hand, Google App Engine provides the following key features:
- Zero to sixty: Scale your app automatically without worrying about managing machines.
- Supercharged APIs: Supercharge your app with services such as Task Queue, XMPP, and Cloud SQL, all powered by the same infrastructure that powers the Google services you use every day.
- You're in control: Manage your application with a simple, web-based dashboard allowing you to customize your app's performance.
"No infrastructure", "Cheap" and "Quick" are the key factors why developers consider AWS Lambda; whereas "Easy to deploy", "Auto scaling" and "Good free plan" are the primary reasons why Google App Engine is favored.
According to the StackShare community, AWS Lambda has a broader approval, being mentioned in 1023 company stacks & 614 developers stacks; compared to Google App Engine, which is listed in 482 company stacks and 345 developer stacks.
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With Cloud Endpoints you can create and deploy mobile backend in one hour or less. And it is free (until you need extra scale). I would not recommend to use Java - python is faster and has all new appengine features.
Pros: everything is in one place: task queue, cron, backend instances for data processing, datastore, mapreduce. Cons: you cannot easily move your code from GAE. Even with special 3rd party services.
With Cloud Endpoints you can create and deploy mobile backend in one hour or less.
I switched my auto chatbot to run in lambda and it was peace !
To use Pusher's presence channel each client must be connected through a backend authentication system. While Pointer doesn't actually have any login based authentication it still needed a backend system to connect users to the proper channel.
A small function was built that only gets called when a user first joins a session. After the user is authenticated they can communicate directly with other clients on the same channel. This made the authentication code the perfect candidate for a serverless function. Using AWS Lambda through Netlify's Functions feature made it a breeze to host.
PaaS for back-end components, including external data ingestion APIs, front-end web service APIs, hosting of static front-end application assets, back-end data processing pipeline microservices, APIs to storage infrastructure (Cloud SQL and Memcached), and data processing pipeline task queues and cron jobs. Task queue fan-out and auto-scaling of back-end microservice instances provide parallelism for high velocity data processing.
checking a swap require a lot of cpu resource, roster normally come out same day of month, every month, at a particular time. Which make very high spike, our flag ship product, iSwap, with the capability looking swap possibility with 10000 other rosters base on user critieria, you need a cloud computing give you this magnitude of computing power. gae did it nicely, user friendly, easy to you, low cost.
We're moving almost the entirety of our backend processes into Lambda. This has given us vast cost savings in terms of pure infrastructure billing - and time worrying about platform and scale. This move has also made our architecture almost entirely event-driven - another huge benefit as our business itself is inherently event-driven.
I mostly use AWS Lambda for triggering DevOps-related actions, like triggering an alarm or a deployment, or scheduling a backup.
I haven’t gone totally “serverless” and I’m not planning to go 100% serverless anytime soon.
But when I do, AWS Lambda will be an important element in my serverless setup.
PrometheanTV uses various Lambda functions to provide back-end capabilities to the platform without the need of deploying servers. Examples include, geo lookup services, and data aggregation services.
Serverless is the future. And AWS Lambda is the most mature FaaS out there. AWS SAM makes it easy to package Lambda as micro-apps.
App engine fills in the gaps in the increasingly smaller case where it's necessary for us to run our own APIs.
Very easy to make cloud computing of ML models , and use containers like Kubernetes.