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Google Compute Engine vs Heroku: What are the differences?

Introduction

This document highlights the key differences between Google Compute Engine and Heroku.

  1. Pricing model: Google Compute Engine offers a pay-as-you-go pricing model, where users are billed based on the resources they consume. On the other hand, Heroku follows a platform-as-a-service (PaaS) pricing model, where the cost is determined by the dyno hours used.

  2. Scalability: Google Compute Engine allows users to scale resources vertically by increasing the size of a virtual machine, or horizontally by adding more virtual machines to a cluster. Heroku, however, supports horizontal scalability by allowing users to add dynos to their applications.

  3. Customization: With Google Compute Engine, users have more control over customizing their virtual machines, as they can choose the operating system, install custom software, and modify network settings. Heroku, being a PaaS, provides limited customization options, as it abstracts away the infrastructure management to provide a simpler development experience.

  4. Managed services: Google Compute Engine offers a wide range of managed services, such as Cloud SQL for managed MySQL and PostgreSQL databases, Cloud Pub/Sub for real-time messaging, and Cloud Storage for object storage. Heroku, on the other hand, provides an integrated platform that includes managed services like Heroku Postgres for databases and Heroku Redis for caching.

  5. Deployment process: Google Compute Engine requires users to manually set up and configure their virtual machines, which involves a more involved deployment process. In contrast, Heroku simplifies the deployment process by providing a Git-based workflow, where users can push their code changes to Heroku and the platform handles the deployment and scaling automatically.

  6. Community support: Google Compute Engine has a large community of users and developers, with extensive documentation, forums, and resources available. Heroku also has a vibrant developer community but is more tightly integrated with the broader Salesforce ecosystem, offering a different support experience.

In summary, Google Compute Engine offers a flexible pricing model, extensive customization options, and a wide range of managed services, making it a suitable choice for users who require greater control and scalability. On the other hand, Heroku provides a simpler deployment process, integrated managed services, and a community that is tightly linked to the Salesforce ecosystem, making it a good option for developers looking for a streamlined development experience.

Decisions about Google Compute Engine and Heroku

I'm transitioning to Render from heroku. The pricing scale matches my usage scale, yet it's just as easy to deploy. It's removed a lot of the devops that I don't like to deal with on setting up my own raw *nix box and makes deployment simple and easy!

Clustering I don't use clustering features at the moment but when i need to set up clustering of nodes and discoverability, render will enable that where Heroku would require that I use an external service like redis.

Restarts The restarts are annoying. I understand the reasoning, but I'd rather watch my service if its got a memory leak and work to fix it than to just assume that it has memory leaks and needs to restart.

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Stephen Fox
Artificial Intelligence Fellow · | 2 upvotes · 196K views

GCE is much more user friendly than EC2, though Amazon has come a very long way since the early days (pre-2010's). This can be seen in how easy it is to edit the storage attached to an instance in GCE: it's under the instance details and is edited inline. In AWS you have to click the instance > click the storage block device (new screen) > click the edit option (new modal) > resize the volume > confirm (new model) then wait a very long time. Google's is nearly instant.

  • In both cases, the instance much be shut down.

There also the preference between "user burden-of-security" and automatic security: AWS goes for the former, GCE the latter.

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Pros of Google Compute Engine
Pros of Heroku
  • 87
    Backed by google
  • 79
    Easy to scale
  • 75
    High-performance virtual machines
  • 57
    Performance
  • 52
    Fast and easy provisioning
  • 15
    Load balancing
  • 12
    Compliance and security
  • 9
    Kubernetes
  • 8
    GitHub Integration
  • 7
    Consistency
  • 4
    Free $300 credit (12 months)
  • 3
    One Click Setup Options
  • 3
    Good documentation
  • 2
    Great integration and product support
  • 2
    Escort
  • 2
    Ease of Use and GitHub support
  • 1
    Nice UI
  • 1
    Easy Snapshot and Backup feature
  • 1
    Integration with mobile notification services
  • 1
    Low cost
  • 1
    Support many OS
  • 1
    Very Reliable
  • 703
    Easy deployment
  • 459
    Free for side projects
  • 374
    Huge time-saver
  • 348
    Simple scaling
  • 261
    Low devops skills required
  • 190
    Easy setup
  • 174
    Add-ons for almost everything
  • 153
    Beginner friendly
  • 150
    Better for startups
  • 133
    Low learning curve
  • 48
    Postgres hosting
  • 41
    Easy to add collaborators
  • 30
    Faster development
  • 24
    Awesome documentation
  • 19
    Simple rollback
  • 19
    Focus on product, not deployment
  • 15
    Natural companion for rails development
  • 15
    Easy integration
  • 12
    Great customer support
  • 8
    GitHub integration
  • 6
    Painless & well documented
  • 6
    No-ops
  • 4
    I love that they make it free to launch a side project
  • 4
    Free
  • 3
    Great UI
  • 3
    Just works
  • 2
    PostgreSQL forking and following
  • 2
    MySQL extension
  • 1
    Security
  • 1
    Able to host stuff good like Discord Bot
  • 0
    Sec

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Cons of Google Compute Engine
Cons of Heroku
    Be the first to leave a con
    • 27
      Super expensive
    • 9
      Not a whole lot of flexibility
    • 7
      No usable MySQL option
    • 7
      Storage
    • 5
      Low performance on free tier
    • 2
      24/7 support is $1,000 per month

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    What is Google Compute Engine?

    Google Compute Engine is a service that provides virtual machines that run on Google infrastructure. Google Compute Engine offers scale, performance, and value that allows you to easily launch large compute clusters on Google's infrastructure. There are no upfront investments and you can run up to thousands of virtual CPUs on a system that has been designed from the ground up to be fast, and to offer strong consistency of performance.

    What is Heroku?

    Heroku is a cloud application platform – a new way of building and deploying web apps. Heroku lets app developers spend 100% of their time on their application code, not managing servers, deployment, ongoing operations, or scaling.

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    What companies use Google Compute Engine?
    What companies use Heroku?
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    What tools integrate with Google Compute Engine?
    What tools integrate with Heroku?

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    What are some alternatives to Google Compute Engine and Heroku?
    Google App Engine
    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.
    DigitalOcean
    We take the complexities out of cloud hosting by offering blazing fast, on-demand SSD cloud servers, straightforward pricing, a simple API, and an easy-to-use control panel.
    Google Cloud Platform
    It helps you build what's next with secure infrastructure, developer tools, APIs, data analytics and machine learning. It is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube.
    Amazon EC2
    It is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale computing easier for developers.
    Microsoft Azure
    Azure is an open and flexible cloud platform that enables you to quickly build, deploy and manage applications across a global network of Microsoft-managed datacenters. You can build applications using any language, tool or framework. And you can integrate your public cloud applications with your existing IT environment.
    See all alternatives