Heroku vs PythonAnywhere

Overview

Heroku

Stacks25.8K

Followers20.5K

Votes3.2K

PythonAnywhere

Stacks90

Followers293

Votes64

Heroku vs PythonAnywhere: What are the differences?

Introduction:

In this article, we will compare the key differences between Heroku and PythonAnywhere, two popular platforms for deploying and hosting web applications.

Deployment Process: The deployment process on Heroku involves pushing code to a Git repository, which then triggers a build and deployment process. On the other hand, PythonAnywhere supports deployment through various methods such as uploading code directly, syncing with Git repositories, or pulling from popular version control systems.
Supported Languages: Heroku supports multiple programming languages including Python, Ruby, Java, PHP, and Node.js, allowing developers to choose the language that best suits their project. PythonAnywhere, as the name suggests, primarily focuses on Python, providing a specialized environment and additional features specific to Python programming.
Server Configuration: Heroku offers a high level of abstraction, automatically managing the underlying infrastructure and server configuration. It provides a platform as a service (PaaS) approach, allowing developers to focus solely on the application development. On the contrary, PythonAnywhere offers more control over the server configuration, enabling users to customize settings such as server software, database configuration, and file permissions.
Pricing Structure: Heroku follows a pay-per-usage pricing model, where users are billed based on the resources consumed by their applications, such as dyno hours, database usage, and add-on services. PythonAnywhere, on the other hand, offers tiered pricing plans that are more focused on the number of web applications, storage space, and computing resources allocated to each account.
Integration with Third-party Services: Heroku provides seamless integration with a wide range of third-party services and add-ons, such as logging, monitoring, email delivery, and database solutions. PythonAnywhere also supports integration with certain third-party services but has a more limited selection compared to Heroku.
Scalability and Performance: Heroku is known for its scalability and can easily handle high traffic and resource-demanding applications. It offers features like horizontal scaling and load balancing to ensure optimal performance. PythonAnywhere, while capable of handling moderate traffic, may have limitations in terms of scalability and performance, particularly for complex or highly concurrent applications.

In summary, Heroku provides a more abstracted and versatile platform, supporting multiple languages and offering seamless integration with third-party services. PythonAnywhere, on the other hand, specializes in Python hosting, providing more control over server configuration but having more limited scalability options.

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Advice on Heroku, PythonAnywhere

Alex

Oct 20, 2020

Decided

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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Comments

Detailed Comparison

Heroku	PythonAnywhere
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.	It's somewhat unique. A small PaaS that supports web apps (Python only) as well as scheduled jobs with shell access. It is an expensive way to tinker and run several small apps.
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 90
Followers 20.5K	Followers 293
Votes 3.2K	Votes 64
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 Storage 7 No usable MySQL option 5 Low performance on free tier	Pros 15 Web apps 11 Easy Setup 8 Great support 8 Shell access 8 Free plan Cons 1 Really small community 1 No root access
Integrations
Mailgun Postmark Loggly Papertrail Redis Cloud Red Hat Codeready Workspaces Nitrous.IO Logentries MongoLab Gemfury	Python

What are some alternatives to Heroku, PythonAnywhere?

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 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.

CapRover

It is an extremely easy to use app/database deployment & web server manager for your NodeJS, Python, PHP, ASP.NET, Ruby, MySQL, MongoDB, Postgres, WordPress (and etc...) applications! It's blazingly fast and very robust as it uses Docker, nginx, LetsEncrypt and NetData under the hood behind its simple-to-use interface.

Related Comparisons

Heroku vs PythonAnywhere: What are the differences?

Introduction:

In this article, we will compare the key differences between Heroku and PythonAnywhere, two popular platforms for deploying and hosting web applications.

Deployment Process: The deployment process on Heroku involves pushing code to a Git repository, which then triggers a build and deployment process. On the other hand, PythonAnywhere supports deployment through various methods such as uploading code directly, syncing with Git repositories, or pulling from popular version control systems.
Supported Languages: Heroku supports multiple programming languages including Python, Ruby, Java, PHP, and Node.js, allowing developers to choose the language that best suits their project. PythonAnywhere, as the name suggests, primarily focuses on Python, providing a specialized environment and additional features specific to Python programming.
Server Configuration: Heroku offers a high level of abstraction, automatically managing the underlying infrastructure and server configuration. It provides a platform as a service (PaaS) approach, allowing developers to focus solely on the application development. On the contrary, PythonAnywhere offers more control over the server configuration, enabling users to customize settings such as server software, database configuration, and file permissions.
Pricing Structure: Heroku follows a pay-per-usage pricing model, where users are billed based on the resources consumed by their applications, such as dyno hours, database usage, and add-on services. PythonAnywhere, on the other hand, offers tiered pricing plans that are more focused on the number of web applications, storage space, and computing resources allocated to each account.
Integration with Third-party Services: Heroku provides seamless integration with a wide range of third-party services and add-ons, such as logging, monitoring, email delivery, and database solutions. PythonAnywhere also supports integration with certain third-party services but has a more limited selection compared to Heroku.
Scalability and Performance: Heroku is known for its scalability and can easily handle high traffic and resource-demanding applications. It offers features like horizontal scaling and load balancing to ensure optimal performance. PythonAnywhere, while capable of handling moderate traffic, may have limitations in terms of scalability and performance, particularly for complex or highly concurrent applications.

Heroku vs PythonAnywhere

Overview