Amazon EC2 vs. Firebase



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Description

What is Amazon EC2?

Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale computing easier for developers.

What is Firebase?

Firebase is a cloud service designed to power real-time, collaborative applications. Simply add the Firebase library to your application to gain access to a shared data structure; any changes you make to that data are automatically synchronized with the Firebase cloud and with other clients within milliseconds.

Want advice about which of these to choose?Ask the StackShare community!

Pros

Why do developers choose Amazon EC2?
Why do you like Amazon EC2?

Why do developers choose Firebase?
Why do you like Firebase?

Cons

What are the cons of using Amazon EC2?
Downsides of Amazon EC2?

What are the cons of using Firebase?
Downsides of Firebase?

Pricing

How much does Amazon EC2 cost?
Amazon EC2 Pricing
How much does Firebase cost?
Firebase Pricing

Companies

What companies use Amazon EC2?
4234 companies on StackShare use Amazon EC2
What companies use Firebase?
932 companies on StackShare use Firebase

Integrations

What tools integrate with Amazon EC2?
85 tools on StackShare integrate with Amazon EC2
What tools integrate with Firebase?
21 tools on StackShare integrate with Firebase

What are some alternatives to Amazon EC2 and Firebase?

  • DigitalOcean - Deploy an SSD cloud server in less than 55 seconds with a dedicated IP and root access.
  • Microsoft Azure - Integrated cloud services and infrastructure to support computing, database, analytics, mobile, and web scenarios.
  • Google Compute Engine - Run large-scale workloads on virtual machines hosted on Google's infrastructure.
  • Linode - Deploy and Manage Linux Virtual Servers in the Linode Cloud.

See all alternatives to Amazon EC2

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Related Stack Decisions
Kestas Barzdaitis
Kestas Barzdaitis
Entrepreneur & Engineer · | 10 upvotes · 8686 views
atCodeFactor
Google Cloud Functions
Azure Functions
AWS Lambda
Docker
Google Compute Engine
Microsoft Azure
Amazon EC2
CodeFactor.io
Kubernetes
#Devops
#AI
#Machinelearning
#Automation
#Startup
#Autoscale
#Containerization
#IAAS
#SAAS

CodeFactor being a #SAAS product, our goal was to run on a cloud-native infrastructure since day one. We wanted to stay product focused, rather than having to work on the infrastructure that supports the application. We needed a cloud-hosting provider that would be reliable, economical and most efficient for our product.

CodeFactor.io aims to provide an automated and frictionless code review service for software developers. That requires agility, instant provisioning, autoscaling, security, availability and compliance management features. We looked at the top three #IAAS providers that take up the majority of market share: Amazon's Amazon EC2 , Microsoft's Microsoft Azure, and Google Compute Engine.

AWS has been available since 2006 and has developed the most extensive services ant tools variety at a massive scale. Azure and GCP are about half the AWS age, but also satisfied our technical requirements.

It is worth noting that even though all three providers support Docker containerization services, GCP has the most robust offering due to their investments in Kubernetes. Also, if you are a Microsoft shop, and develop in .NET - Visual Studio Azure shines at integration there and all your existing .NET code works seamlessly on Azure. All three providers have serverless computing offerings (AWS Lambda, Azure Functions, and Google Cloud Functions). Additionally, all three providers have machine learning tools, but GCP appears to be the most developer-friendly, intuitive and complete when it comes to #Machinelearning and #AI.

The prices between providers are competitive across the board. For our requirements, AWS would have been the most expensive, GCP the least expensive and Azure was in the middle. Plus, if you #Autoscale frequently with large deltas, note that Azure and GCP have per minute billing, where AWS bills you per hour. We also applied for the #Startup programs with all three providers, and this is where Azure shined. While AWS and GCP for startups would have covered us for about one year of infrastructure costs, Azure Sponsorship would cover about two years of CodeFactor's hosting costs. Moreover, Azure Team was terrific - I felt that they wanted to work with us where for AWS and GCP we were just another startup.

In summary, we were leaning towards GCP. GCP's advantages in containerization, automation toolset, #Devops mindset, and pricing were the driving factors there. Nevertheless, we could not say no to Azure's financial incentives and a strong sense of partnership and support throughout the process.

Bottom line is, IAAS offerings with AWS, Azure, and GCP are evolving fast. At CodeFactor, we aim to be platform agnostic where it is practical and retain the flexibility to cherry-pick the best products across providers.

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