Overview

AWS Lambda

Stacks24.4K

Followers18.8K

Votes432

Cloud Functions for Firebase

Stacks477

Followers397

Votes6

AWS Lambda vs Cloud Functions for Firebase: What are the differences?

Introduction

AWS Lambda and Cloud Functions for Firebase are two popular serverless computing platforms. Both platforms offer the ability to run code without the need to provision or manage servers. However, there are key differences between AWS Lambda and Cloud Functions for Firebase that are worth considering when choosing a serverless platform for your application.

Pricing: AWS Lambda offers a pay-as-you-go pricing model, where you are charged based on the number of requests and the duration of each request. On the other hand, Cloud Functions for Firebase has a usage-based pricing model, where you are charged based on the number of invocations, compute time, and network egress. The pricing structure and rates for each platform can significantly impact the cost of running your serverless functions.
Vendor lock-in: AWS Lambda is a service provided by Amazon Web Services (AWS), while Cloud Functions for Firebase is part of Google Cloud Platform (GCP). Choosing one platform over the other may result in vendor lock-in, as each platform has its unique set of features and integrations. Consider the ecosystem and services provided by each platform to ensure it aligns with your project requirements and the larger technology stack.
Language support: AWS Lambda supports a wide range of programming languages, including JavaScript, Python, Java, C#, and more. Cloud Functions for Firebase, on the other hand, primarily supports JavaScript. While you can use other languages with Cloud Functions for Firebase, it requires additional configuration and setup. The language support provided by each platform is important to consider depending on your team's skillset and the compatibility with your existing codebase.
Trigger options: Both AWS Lambda and Cloud Functions for Firebase offer a variety of trigger options, such as HTTP requests, events from cloud services, and database changes. However, Cloud Functions for Firebase has better native integration with Firebase services like Firestore and Realtime Database, making it easier to trigger functions based on changes in your Firebase data. AWS Lambda, on the other hand, provides integrations with a wider range of AWS services and can be used in more general-purpose scenarios.
Runtime environment: AWS Lambda allows you to define the runtime environment for your functions, providing more flexibility in terms of choosing the specific version of the language runtime and any required dependencies. Cloud Functions for Firebase, on the other hand, uses a managed runtime environment that abstracts away the infrastructure details, allowing you to focus solely on writing the function logic. Depending on your requirements, the level of control over the runtime environment may influence your choice of platform.
Community and documentation: Both AWS Lambda and Cloud Functions for Firebase have active communities and extensive documentation resources. However, AWS Lambda has a larger and more mature community with a wide range of third-party libraries, developer tools, and resources available. This can be beneficial if you require advanced features or if you need assistance from the community to solve specific challenges.

In Summary, AWS Lambda and Cloud Functions for Firebase differ in pricing models, language support, trigger options, runtime environments, and the size of their respective communities. Consider these differences when choosing a serverless platform for your application, as they can impact the cost, flexibility, ease of development, and availability of resources and community support.

Advice on AWS Lambda, Cloud Functions for Firebase

Tim

CTO at Checkly Inc.

Sep 18, 2019

Needs adviceon

Heroku

AWS Lambda

When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda . The short story:

Developer Experience trumps everything.
AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
If you need geographic spread, AWS is lonely at the top.

The setup

Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup. Everything was on the table. But we crossed out a lot quite quickly:

Pure, uncut, self hosted Kubernetes — way too much complexity
Managed Kubernetes in various flavors — still too much complexity
Zeit — Maybe, but no Docker support
Elastic Beanstalk — Maybe, bit old but does the job
Heroku
Lambda

It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly! But when do you pick which model?

I chopped that question up into the following categories:

Developer Experience / DX 🤓
Ops Experience / OX 🐂 (?)
Cost 💵
Lock in 🔐

Read the full post linked below for all details

357k views357k

Comments

Mark

Nov 2, 2020

Needs adviceon

Microsoft Azure

Need advice on what platform, systems and tools to use.

Evaluating whether to start a new digital business for which we will need to build a website that handles all traffic. Website only right now. May add smartphone apps later. No desktop app will ever be added. Website to serve various countries and languages. B2B and B2C type customers. Need to handle heavy traffic, be low cost, and scale well.

We are open to either build it on AWS or on Microsoft Azure.

Apologies if I'm leaving out some info. My first post. :) Thanks in advance!

133k views133k

Comments

Cory

Mar 28, 2021

Decided

Netlfiy Functions uses AWS Lambda under the hood, but Netlify adds some nice sugar. The biggest advantage is the local development experience with netlify-cli. This allows you to run your functions locally with local configuration or pull configs from the Netlify dashboard. I built a health-check endpoint in about 2 minutes, and my send-email function in less than an hour.

28.2k views28.2k

Comments

Detailed Comparison

AWS Lambda	Cloud Functions for Firebase
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.	Cloud Functions for Firebase lets you create functions that are triggered by Firebase products, such as changes to data in the Realtime Database, uploads to Cloud Storage, new user sign ups via Authentication, and conversion events in Analytics.
Extend other AWS services with custom logic;Build custom back-end services;Completely Automated Administration;Built-in Fault Tolerance;Automatic Scaling;Integrated Security Model;Bring Your Own Code;Pay Per Use;Flexible Resource Model	-
Statistics
Stacks 24.4K	Stacks 477
Followers 18.8K	Followers 397
Votes 432	Votes 6
Pros & Cons
Pros 129 No infrastructure 83 Cheap 70 Quick 59 Stateless 47 No deploy, no server, great sleep Cons 7 Cant execute ruby or go 3 Compute time limited 1 Can't execute PHP w/o significant effort	Pros 4 Up and running 1 Affordable 1 Multi-region
Integrations
No integrations available	Firebase Google Cloud Storage Google Cloud Functions

What are some alternatives to AWS Lambda, Cloud Functions for Firebase?

Azure Functions

Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.

Google Cloud Run

A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

Serverless

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

Google Cloud Functions

Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running

Knative

Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center

OpenFaaS

Serverless Functions Made Simple for Docker and Kubernetes

Nuclio

nuclio is portable across IoT devices, laptops, on-premises datacenters and cloud deployments, eliminating cloud lock-ins and enabling hybrid solutions.

Apache OpenWhisk

OpenWhisk is an open source serverless platform. It is enterprise grade and accessible to all developers thanks to its superior programming model and tooling. It powers IBM Cloud Functions, Adobe I/O Runtime, Naver, Nimbella among others.

AWS Batch

It enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. It dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted.

Fission

Write short-lived functions in any language, and map them to HTTP requests (or other event triggers). Deploy functions instantly with one command. There are no containers to build, and no Docker registries to manage.