AWS Lambda vs. Google App Engine

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
AWS Lambda
Score 8.7 out of 10
N/A
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 9.2 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
Pricing
AWS LambdaGoogle App Engine
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
Offerings
Pricing Offerings
AWS LambdaGoogle 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
AWS LambdaGoogle App Engine
Features
AWS LambdaGoogle App Engine
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
AWS Lambda
9.3
Ratings
3% below category average
Google App Engine
-
Ratings
Multiple Access Permission Levels (Create, Read, Delete)9.00 Ratings00 Ratings
Single Sign-On (SSO)9.50 Ratings00 Ratings
Reporting & Analytics
Comparison of Reporting & Analytics features of Product A and Product B
AWS Lambda
6.1
Ratings
4% below category average
Google App Engine
-
Ratings
Dashboards6.70 Ratings00 Ratings
Standard reports6.50 Ratings00 Ratings
Custom reports5.00 Ratings00 Ratings
Function as a Service (FaaS)
Comparison of Function as a Service (FaaS) features of Product A and Product B
AWS Lambda
7.9
Ratings
3% below category average
Google App Engine
-
Ratings
Programming Language Diversity9.00 Ratings00 Ratings
Runtime API Authoring8.30 Ratings00 Ratings
Function/Database Integration8.30 Ratings00 Ratings
DevOps Stack Integration6.00 Ratings00 Ratings
Platform-as-a-Service
Comparison of Platform-as-a-Service features of Product A and Product B
AWS Lambda
-
Ratings
Google App Engine
8.7
Ratings
9% above category average
Ease of building user interfaces00 Ratings9.00 Ratings
Scalability00 Ratings9.00 Ratings
Platform management overhead00 Ratings9.00 Ratings
Workflow engine capability00 Ratings9.00 Ratings
Platform access control00 Ratings9.00 Ratings
Services-enabled integration00 Ratings8.00 Ratings
Development environment creation00 Ratings9.00 Ratings
Development environment replication00 Ratings8.00 Ratings
Issue monitoring and notification00 Ratings9.00 Ratings
Issue recovery00 Ratings9.00 Ratings
Upgrades and platform fixes00 Ratings8.00 Ratings
Best Alternatives
AWS LambdaGoogle App Engine
Small Businesses
IBM Cloud Functions
IBM Cloud Functions
Score 8.0 out of 10
AWS Lambda
AWS Lambda
Score 8.7 out of 10
Medium-sized Companies
Red Hat OpenShift
Red Hat OpenShift
Score 9.3 out of 10
Red Hat OpenShift
Red Hat OpenShift
Score 9.3 out of 10
Enterprises
Red Hat OpenShift
Red Hat OpenShift
Score 9.3 out of 10
Red Hat OpenShift
Red Hat OpenShift
Score 9.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
AWS LambdaGoogle App Engine
Likelihood to Recommend
9.3
(0 ratings)
8.0
(0 ratings)
Likelihood to Renew
-
(0 ratings)
8.3
(0 ratings)
Usability
9.0
(0 ratings)
7.7
(0 ratings)
Performance
-
(0 ratings)
10.0
(0 ratings)
Support Rating
8.7
(0 ratings)
8.4
(0 ratings)
Implementation Rating
-
(0 ratings)
8.0
(0 ratings)
User Testimonials
AWS LambdaGoogle App Engine
Likelihood to Recommend
Scenarios where AWS Lambda is well suited: 1. When we need to run a periodic task few times in a day or every hour, we may deploy it on AWS Lambda so it would not increase load on our server which is handling client requests and at the same time we don't have to pay for AWS Lambda when it is not running. So, overall we only pay for few function invocations. 2. When some compute intensive processing is to be done but the number of requests per unit of time fluctuates. For example, we had deployed an AWS Lambda for processing images into different sizes and storing them on AWS S3 once user uploads them. Now, this is something that may happen few times every hour on a particular day or may not happen even once on other days. To handle this kind of tasks AWS Lambda is a better choice as we don't have to pay for the idle time of the server and also we don't have to worry about scaling when the load is high. Scenarios where AWS Lambda is not appropriate to use: 1. When we expect a large request volume continuously on the server. 2. When we don't want latency even in case of concurrent requests.
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Google App Engine is especially well suited for situations where there is a variable workload during the day, e.g. inbound task processing with task queues. In this situation queues can be setup with parameters governing the process speed/scaling which allows you to easily balance performance with cost and meet a good balance.
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Pros
  • AWS Lambda is a welcoming platform, supporting several languages, including Java, Go, PowerShell, Node.js, C#, Python, and Ruby. And if you need to deploy a Lambda function in another language, AWS offers a Runtime API for integration.
  • We really appreciate how AWS Lambda is always-on for our functions, with only a brief "cold-start" waiting period the first time a function is called after being dormant.
  • In addition to only generating costs when it's actually being used, AWS Lambda really puts the "serverless" in serverless architecture, offering turnkey scaleability and high availability for our code with zero effort on our part.
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  • Building an application that uses Google's Authentication, means users no longer need to remember an different user id and password. Once they are logged into to Google, they can seamlessly access your application hosted on Google App Engine.
  • Google App Engine automatically scales up and down. SO if your application receives a spike in user traffic, App Engine automatically launches additional instances of your application to cater for the increased traffic. Once App Engine detects that the spike is usage is over, it automatically scales down to handle the current traffic.
  • Google App Engine can be easily integrated with Google Cloud SQL, Google Compute Engine, Google Cloud Storage etc, so that you can build out a full application using one or more of Google's Cloud Platform products.
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Cons
  • The UI and Developer experience is not so great. IF you use an abstraction like Serverless Application Model (SAM), things get pretty easy, but it's still AWS UI/DX you're working with after that (which is to say, not their strength).
  • Documentation is always a mixed bag. Sometimes it's just easier to google your specific problem and see how others have solved it. This can be much faster than trying to find an example that may or may not be there in the documentation (which oftentimes has multiple versions and revisions).
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  • For beginners, there is a learning curve that can be reduced by decluttering the functionalities.
  • For much big migrations it takes to a lot of time to deploy which can be reduced.
  • The scaling of applications based on the user count is not seamless and it requires improvement.
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Likelihood to Renew
No answers on this topic
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.
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Usability
It is very easy to get started with AWS Lambda and create your first function. The user interface makes it easy to add AWS services to be inputs or outputs to the function, meaning it can be configured in many different ways for different needs. This makes it ideal for various scenarios in AWS.
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Google App Engine is very intuitive. It has the common programming language most would use. Google is a dependable name and I have not had issues with their servers being down....ever. You can safely use their service and store your data on their servers without worrying about downtime or loss of data.
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Support Rating
As this is a product where a great part of errors can be at the source code level, AWS support team doesn't dive that further. I mean they don't evaluate problems more complex related to your code, [which] is totally understandable, but this make[s] debug process more tough and painful.
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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.
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Alternatives Considered
It's fine, it works as the others would have, except EC2. We are migrating back to EC2 for dedicated compute because we have scaled to a point where we have consistent traffic. The tradeoff of maintaining infrastructure in-house outweighs the benefits of moving quickly through our roadmap.
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App Engine is a much more streamlined system than EC2. There is a fundamental difference between them, but they are used for basically the same thing as far a I could tell -- to serve applications EC2 is certainly more complicated, but if offers more machine-level control if that's what you need. It can tend to cost more as well. App Engine is far more straightforward but there are limitations if you need to change the environment. But even then, Google Compute Engine also compares to EC2 and stays within GCP.
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Return on Investment
  • We have simplified log fiie ingestion using Lambda functions. The return has been less time worrying about getting logs from source to ingestion; one the process is in place the team is nearly 100% hands off.
  • We have begun taking a more API focused approach by using API Gateway as the interface to business processes and Lambda as the back end compute. Moving away from server based back ends places us on a path to reducing overall spend in compute costs.
  • Lambda functions allow us to easily interface with third party services through APIs. This simplifies access management since the function can be granted permissions and access to the function can be gated with API keys and other authentication methods.
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  • App Engine can scale basically infinitely so our users can always expect fast responsiveness.
  • App Engine has saved us money by only using the resources we need when we need them.
  • The security and IAM policies surrounding App Engine have saved a lot of head aches.
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