Google Cloud Functions vs Heroku

Overview

Heroku

Stacks25.8K

Followers20.5K

Votes3.2K

Google Cloud Functions

Stacks479

Followers479

Votes25

Google Cloud Functions vs Heroku: What are the differences?

Google Cloud Functions vs Heroku

Google Cloud Functions and Heroku are two popular platforms for deploying and running applications. While both offer similar functionalities, there are several key differences between them.

Scalability and Infrastructure: One major difference between Google Cloud Functions and Heroku is the scalability and underlying infrastructure. Google Cloud Functions is built on a serverless architecture, which means it automatically scales up or down based on demand, allowing for efficient resource utilization. In contrast, Heroku uses a more traditional infrastructure where you need to manually configure and allocate resources.
Pricing and Billing: Another important difference is the pricing and billing model. Google Cloud Functions has a pay-as-you-go pricing model, where you are billed based on the number of invocations and the resources used during the execution. On the other hand, Heroku offers a variety of pricing plans that are based on the number of dynos (containerized application instances) and additional addons.
Supported Languages and Runtimes: Google Cloud Functions supports a wide range of programming languages including Node.js, Python, and Java. It also provides the flexibility to bring your own runtime and environment. Heroku, on the other hand, supports a broader range of languages, including Ruby, PHP, and Go, and provides a more comprehensive set of language-specific buildpacks and addons.
Deployment Options: Google Cloud Functions offers a variety of deployment options, including direct code deployment, integration with Cloud Source Repositories, and deployment through the command-line interface. Heroku also provides multiple deployment options, but it focuses more on Git-based deployments, allowing you to deploy code directly from your Git repo.
Integration and Ecosystem: Google Cloud Functions is tightly integrated with other Google Cloud services, such as Firebase, BigQuery, and Cloud Pub/Sub, providing a seamless experience for developing and integrating distributed systems. Heroku, on the other hand, has its own ecosystem and marketplace of addons, which can be easily integrated into your application for added functionalities.
Managed Services and DevOps: Google Cloud Functions is a fully managed serverless platform, which means that you don't need to worry about infrastructure setup, patching, or scaling. It abstracts away the underlying infrastructure and provides automatic scaling and fault tolerance. Heroku also offers a managed platform, but it provides more control over the infrastructure and configuration, allowing for more advanced DevOps practices.

In summary, Google Cloud Functions and Heroku differ in terms of scalability, pricing, supported languages, deployment options, integration, and underlying infrastructure. The choice between them depends on your specific requirements, application needs, and familiarity with the respective platforms.

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Advice on Heroku, Google Cloud Functions

Clifford

Software Engineer at Bidvest Advisory Services

Mar 28, 2020

Decided

Run cloud service containers instead of cloud-native services

Running containers means that your microservices are not "cooked" into a cloud provider's architecture.
Moving from one cloud to the next means that you simply spin up new instances of your containers in the new cloud using that cloud's container service.
Start redirecting your traffic to the new resources.
Turn off the containers in the cloud you migrated from.

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Detailed Comparison

Heroku	Google Cloud Functions
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.	Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running
Agile deployment for Ruby, Node.js, Clojure, Java, Python, Go and Scala.;Run and scale any type of app.;Total visibility across your entire app.;Erosion-resistant architecture. Rich control surfaces.	-
Statistics
Stacks 25.8K	Stacks 479
Followers 20.5K	Followers 479
Votes 3.2K	Votes 25
Pros & Cons
Pros 703 Easy deployment 459 Free for side projects 374 Huge time-saver 348 Simple scaling 261 Low devops skills required Cons 27 Super expensive 9 Not a whole lot of flexibility 7 No usable MySQL option 7 Storage 5 Low performance on free tier	Pros 7 Serverless Applications 5 Its not AWS 4 Simplicity 3 Free Tiers and Trainging 2 Simple config with GitLab CI/CD Cons 1 Node.js only 0 Typescript Support 0 Blaze, pay as you go
Integrations
Mailgun Postmark Loggly Papertrail Redis Cloud Red Hat Codeready Workspaces Nitrous.IO Logentries MongoLab Gemfury	Firebase Google Cloud Storage Stackdriver

What are some alternatives to Heroku, Google Cloud Functions?

Clever Cloud

Clever Cloud is a polyglot cloud application platform. The service helps developers to build applications with many languages and services, with auto-scaling features and a true pay-as-you-go pricing model.

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.

Red Hat OpenShift

OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications.

AWS Lambda

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.

AWS Elastic Beanstalk

Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring.

Render

Render is a unified platform to build and run all your apps and websites with free SSL, a global CDN, private networks and auto deploys from Git.

Hasura

An open source GraphQL engine that deploys instant, realtime GraphQL APIs on any Postgres database.

Cloud 66

Cloud 66 gives you everything you need to build, deploy and maintain your applications on any cloud, without the headache of dealing with "server stuff". Frameworks: Ruby on Rails, Node.js, Jamstack, Laravel, GoLang, and more.

Jelastic

Jelastic is a Multi-Cloud DevOps PaaS for ISVs, telcos, service providers and enterprises needing to speed up development, reduce cost of IT infrastructure, improve uptime and security.

Dokku

It is an extensible, open source Platform as a Service that runs on a single server of your choice. It helps you build and manage the lifecycle of applications from building to scaling.

Related Comparisons

Google Cloud Functions vs Heroku: What are the differences?

Google Cloud Functions vs Heroku

Google Cloud Functions and Heroku are two popular platforms for deploying and running applications. While both offer similar functionalities, there are several key differences between them.

Scalability and Infrastructure: One major difference between Google Cloud Functions and Heroku is the scalability and underlying infrastructure. Google Cloud Functions is built on a serverless architecture, which means it automatically scales up or down based on demand, allowing for efficient resource utilization. In contrast, Heroku uses a more traditional infrastructure where you need to manually configure and allocate resources.
Pricing and Billing: Another important difference is the pricing and billing model. Google Cloud Functions has a pay-as-you-go pricing model, where you are billed based on the number of invocations and the resources used during the execution. On the other hand, Heroku offers a variety of pricing plans that are based on the number of dynos (containerized application instances) and additional addons.
Supported Languages and Runtimes: Google Cloud Functions supports a wide range of programming languages including Node.js, Python, and Java. It also provides the flexibility to bring your own runtime and environment. Heroku, on the other hand, supports a broader range of languages, including Ruby, PHP, and Go, and provides a more comprehensive set of language-specific buildpacks and addons.
Deployment Options: Google Cloud Functions offers a variety of deployment options, including direct code deployment, integration with Cloud Source Repositories, and deployment through the command-line interface. Heroku also provides multiple deployment options, but it focuses more on Git-based deployments, allowing you to deploy code directly from your Git repo.
Integration and Ecosystem: Google Cloud Functions is tightly integrated with other Google Cloud services, such as Firebase, BigQuery, and Cloud Pub/Sub, providing a seamless experience for developing and integrating distributed systems. Heroku, on the other hand, has its own ecosystem and marketplace of addons, which can be easily integrated into your application for added functionalities.
Managed Services and DevOps: Google Cloud Functions is a fully managed serverless platform, which means that you don't need to worry about infrastructure setup, patching, or scaling. It abstracts away the underlying infrastructure and provides automatic scaling and fault tolerance. Heroku also offers a managed platform, but it provides more control over the infrastructure and configuration, allowing for more advanced DevOps practices.

Google Cloud Functions vs Heroku

Overview

Google Cloud Functions vs Heroku: What are the differences?