aws-lambda vs firebase-functions
Serverless Function Frameworks Comparison
1 Year
aws-lambdafirebase-functions
What's Serverless Function Frameworks?

Serverless function frameworks allow developers to run code in response to events without managing servers. They provide a way to deploy and execute small units of code, known as functions, in a scalable manner. Both AWS Lambda and Firebase Functions enable developers to build applications that respond to HTTP requests, database changes, and other events, but they cater to different ecosystems and use cases. AWS Lambda is part of the broader AWS ecosystem, providing extensive integration with various AWS services, while Firebase Functions is tightly integrated with Firebase and Google Cloud, focusing on mobile and web app development.

Package Weekly Downloads Trend
Github Stars Ranking
Stat Detail
Package
Downloads
Stars
Size
Issues
Publish
License
aws-lambda1,117,61722-103 years agoMIT
firebase-functions504,1711,034900 kB9416 days agoMIT
Feature Comparison: aws-lambda vs firebase-functions

Ecosystem Integration

  • aws-lambda:

    AWS Lambda seamlessly integrates with a wide range of AWS services, such as S3, DynamoDB, and API Gateway. This allows developers to create complex workflows and architectures that leverage the full power of AWS, making it suitable for enterprise-level applications.

  • firebase-functions:

    Firebase Functions is deeply integrated with Firebase services, allowing for easy triggering of functions based on Firestore changes, Authentication events, and more. This tight integration simplifies the development process for mobile and web applications that rely on Firebase.

Deployment and Management

  • aws-lambda:

    AWS Lambda provides a robust set of tools for deployment and management, including AWS SAM (Serverless Application Model) and the Serverless Framework. These tools allow for versioning, monitoring, and scaling of functions, making it easier to manage complex applications.

  • firebase-functions:

    Firebase Functions offers a straightforward deployment process via the Firebase CLI, enabling quick updates and management of functions. The Firebase console provides an intuitive interface for monitoring function performance and logs, making it user-friendly for developers.

Cold Start Performance

  • aws-lambda:

    AWS Lambda has a reputation for longer cold start times, especially for functions that are not invoked frequently. However, AWS offers provisioned concurrency to mitigate this issue, allowing functions to remain warm and ready to respond quickly.

  • firebase-functions:

    Firebase Functions generally has shorter cold start times compared to AWS Lambda, especially for functions that are invoked frequently. This can lead to a more responsive experience for users, particularly in mobile applications.

Pricing Model

  • aws-lambda:

    AWS Lambda pricing is based on the number of requests and the duration of execution, with a free tier available. This model can be cost-effective for applications with variable workloads, but costs can accumulate with high usage.

  • firebase-functions:

    Firebase Functions also follows a pay-as-you-go pricing model based on invocations and compute time, with generous free tier limits. This makes it an attractive option for developers building small to medium-sized applications.

Language Support

  • aws-lambda:

    AWS Lambda supports multiple programming languages, including Node.js, Python, Java, Go, and C#. This flexibility allows developers to use their preferred languages and frameworks, making it suitable for diverse teams.

  • firebase-functions:

    Firebase Functions primarily supports JavaScript and TypeScript, which aligns well with the Firebase ecosystem. This focus on JavaScript makes it a natural choice for web developers familiar with these languages.

How to Choose: aws-lambda vs firebase-functions
  • aws-lambda:

    Choose AWS Lambda if you are already using AWS services or need advanced features like custom runtimes, VPC integration, or extensive monitoring capabilities. It is suitable for applications that require high scalability and complex event processing.

  • firebase-functions:

    Choose Firebase Functions if you are building a mobile or web application that heavily relies on Firebase services, such as Firestore or Firebase Authentication. It is ideal for developers looking for ease of use and rapid deployment within the Firebase ecosystem.

README for aws-lambda

cli-lambda-deploy

Command line tool deploy code to AWS Lambda.

npm test Downloads Downloads Downloads

Notes

Versions prior to 1.0.5 suffer from "Command Injection" vulnerability,
thanks snyk.io and Song Li of Johns Hopkins University for reporting.

Installation

npm install -g aws-lambda

WARN: upgrading to v1.0.0 will remove your function environment and layers if they are not defined in the config file

Config file

  • PATH must point to your code folder and is relative to the config file
  • PATH can be relative or absolute
  • If not set, Runtime defaults to nodejs10.x
  • If not set, FunctionName defaults to the name of the config file ("my-function" in this case)
  • You can use Ref to reference environment variables in the form of env.YOUR_ENVIRONMENT_NAME
  • lambda deploy <file.lambda> credentials needs permissions to CreateFunction, UpdateFunctionConfiguration and UpdateFunctionCode
  • lambda delete <file.lambda> credentials needs permissions to DeleteFunction
  • lambda invoke <file.lambda> credentials needs permissions to InvokeFunction

Sample JSON config


{
	"PATH": "./test-function",
	"AWS_KEY": { "Ref" : "env.AWS_ACCESS_KEY_ID" },,
	"AWS_SECRET": { "Ref" : "env.AWS_SECRET_ACCESS_KEY"},
	"AWS_REGION": "us-east-1",

	"FunctionName": "test-lambda",
	"Role": "your_amazon_role",
	"Runtime": "nodejs10.x",
	"Handler": "index.handler",
	"MemorySize": "128",
	"Timeout": "3",
	"Environment": {
		"Variables": {
			"Hello": "World",
		}
	},
	"Layers": [
		"arn:aws:lambda:eu-central-1:452980636694:layer:awspilot-dynamodb-2_0_0-beta:1"
	],
	"Tags": {
		"k1": "v1",
		"k2": "v2"
	},
	"Description": ""
}

Sample YAML config

# unlike json, comments are allowed in yaml, yey!
# remember to use spaces not tabs 😞
PATH: ./new-function
AWS_KEY:  !Ref "env.lambda_deploy_aws_key"
AWS_SECRET: !Ref "env.lambda_deploy_aws_secret"
AWS_REGION: "eu-central-1"

FunctionName: new-function-v12
Role: "arn:aws:iam::452980636694:role/CliLambdaDeploy-TestRole-1H89NZ845HHBK"
Runtime: "nodejs8.10"
Handler: "index.handler"
MemorySize: "128"
Timeout: "3"
Environment:
    Variables:
        Hello: "World"
Layers:
    - "arn:aws:lambda:eu-central-1:452980636694:layer:awspilot-dynamodb-2_0_0-beta:1"
Tags:
    k1: v1
    k2: v2
Description: ""

Deploy from Local to AWS Lambda

// if installed globally then
$ lambda deploy /path/to/my-function.lambda
$ lambda deploy ../configs/my-function.lambda

// if 'npm installed' without the -g then you must use the full path
$ node_modules/.bin/lambda /path/to/my-function.lambda

// you can also add it in your scripts section of your package.json scripts: { "deploy-func1": "lambda deploy ../config/func1.lambda" }
$ npm run deploy-func1

Watch config file

aws-lambda can also watch the config file and the code folder specified in the config.PATH for changes and re-reploy on change

$ lambda start ../configs/my-function.lambda