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  1. Stackups
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  3. Task Scheduling
  4. Workflow Manager
  5. Airflow vs Github Actions

Airflow vs Github Actions

OverviewDecisionsComparisonAlternatives

Overview

Airflow
Airflow
Stacks1.7K
Followers2.8K
Votes128
GitHub Actions
GitHub Actions
Stacks48.2K
Followers3.1K
Votes27

Airflow vs Github Actions: What are the differences?

Key Differences between Airflow and Github Actions

Introduction

Airflow is a platform to programmatically author, schedule, and monitor workflows, while Github Actions is a platform for automating workflows in a Github repository. The key differences between Airflow and Github Actions are as follows:

  1. Workflow Orchestration: Airflow is specifically designed for workflow orchestration, providing a rich set of tools and features to create, schedule, and manage complex workflows. On the other hand, Github Actions focuses more on automating smaller, task-based workflows within the context of a Github repository.

  2. Flexibility and Extensibility: Airflow offers a high degree of flexibility and extensibility, allowing users to define their own custom operators and hooks to integrate with various systems. This gives Airflow the ability to handle a wide range of use cases and integrate with different technologies. In contrast, Github Actions provides a limited set of pre-defined actions and lacks the same level of flexibility to customize and extend the platform.

  3. Integration with External Systems: Airflow provides built-in integrations with various external systems and services, such as databases, cloud platforms, and messaging systems. It offers operators and hooks that can easily connect to these systems and perform actions. Github Actions, on the other hand, has a more limited range of integrations and requires additional setup and configuration to connect to external systems.

  4. Community and Ecosystem: Airflow has a large and active community, with a wide range of plugins, extensions, and resources available. This allows users to leverage existing solutions and knowledge when using Airflow. Github Actions, being a newer platform, has a smaller community and ecosystem, with fewer resources and integrations available compared to Airflow.

  5. Scalability and Performance: Airflow is designed to handle large-scale workflows and high-throughput processing, with features like task parallelism, distributed execution, and scalability. It can efficiently handle complex dependencies and run workflows across multiple machines or clusters. Github Actions, on the other hand, is more suited for smaller-scale workflows and lacks the same level of scalability and performance as Airflow.

  6. Pricing and Deployment: Airflow is typically deployed on dedicated infrastructure, either on-premises or in the cloud, and requires setup and maintenance of the infrastructure. It may incur additional costs for infrastructure and scaling. Github Actions, being a cloud-native platform, is hosted by Github and is available as part of Github's pricing plans. It provides a simpler setup and deployment process, without the need for managing infrastructure.

In summary, Airflow is a powerful workflow orchestration platform with extensive capabilities and flexibility, designed for complex and large-scale workflows. Github Actions, on the other hand, is a more lightweight and task-based automation platform, tightly integrated with Github repositories, but with more limited flexibility and scalability.

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Advice on Airflow, GitHub Actions

Somnath
Somnath

Engineering Leader at Altimetrik Corp.

Jun 25, 2020

Needs adviceonCircleCICircleCIDrone.ioDrone.ioGitHub ActionsGitHub Actions

I am in the process of evaluating CircleCI, Drone.io, and GitHub Actions to cover my #CI/ #CD needs. I would appreciate your advice on comparative study w.r.t. attributes like language-Inclusive support, code-base integration, performance, cost, maintenance, support, ease of use, ability to deal with big projects, etc. based on actual industry experience.

Thanks in advance!

1.82M views1.82M
Comments
Anonymous
Anonymous

Jan 19, 2020

Needs advice

I am so confused. I need a tool that will allow me to go to about 10 different URLs to get a list of objects. Those object lists will be hundreds or thousands in length. I then need to get detailed data lists about each object. Those detailed data lists can have hundreds of elements that could be map/reduced somehow. My batch process dies sometimes halfway through which means hours of processing gone, i.e. time wasted. I need something like a directed graph that will keep results of successful data collection and allow me either pragmatically or manually to retry the failed ones some way (0 - forever) times. I want it to then process all the ones that have succeeded or been effectively ignored and load the data store with the aggregation of some couple thousand data-points. I know hitting this many endpoints is not a good practice but I can't put collectors on all the endpoints or anything like that. It is pretty much the only way to get the data.

294k views294k
Comments

Detailed Comparison

Airflow
Airflow
GitHub Actions
GitHub Actions

Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.

It makes it easy to automate all your software workflows, now with world-class CI/CD. Build, test, and deploy your code right from GitHub. Make code reviews, branch management, and issue triaging work the way you want.

Dynamic: Airflow pipelines are configuration as code (Python), allowing for dynamic pipeline generation. This allows for writting code that instantiate pipelines dynamically.;Extensible: Easily define your own operators, executors and extend the library so that it fits the level of abstraction that suits your environment.;Elegant: Airflow pipelines are lean and explicit. Parameterizing your scripts is built in the core of Airflow using powerful Jinja templating engine.;Scalable: Airflow has a modular architecture and uses a message queue to talk to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity.
Multiple workflow files support; Free and open source; Workflow run interface; Search for actions in GitHub Marketplace; Integrated with Github's Checks API; Logs and artifacts downloading support
Statistics
Stacks
1.7K
Stacks
48.2K
Followers
2.8K
Followers
3.1K
Votes
128
Votes
27
Pros & Cons
Pros
  • 53
    Features
  • 14
    Task Dependency Management
  • 12
    Cluster of workers
  • 12
    Beautiful UI
  • 10
    Extensibility
Cons
  • 2
    Running it on kubernetes cluster relatively complex
  • 2
    Observability is not great when the DAGs exceed 250
  • 2
    Open source - provides minimum or no support
  • 1
    Logical separation of DAGs is not straight forward
Pros
  • 8
    Integration with GitHub
  • 5
    Free
  • 3
    Easy to duplicate a workflow
  • 3
    Ready actions in Marketplace
  • 2
    Configs stored in .github
Cons
  • 5
    Lacking [skip ci]
  • 4
    Lacking allow failure
  • 3
    Lacking job specific badges
  • 2
    No ssh login to servers
  • 1
    No Deployment Projects
Integrations
No integrations available
GitHub
GitHub

What are some alternatives to Airflow, GitHub Actions?

Jenkins

Jenkins

In a nutshell Jenkins CI is the leading open-source continuous integration server. Built with Java, it provides over 300 plugins to support building and testing virtually any project.

Travis CI

Travis CI

Free for open source projects, our CI environment provides multiple runtimes (e.g. Node.js or PHP versions), data stores and so on. Because of this, hosting your project on travis-ci.com means you can effortlessly test your library or applications against multiple runtimes and data stores without even having all of them installed locally.

Codeship

Codeship

Codeship runs your automated tests and configured deployment when you push to your repository. It takes care of managing and scaling the infrastructure so that you are able to test and release more frequently and get faster feedback for building the product your users need.

CircleCI

CircleCI

Continuous integration and delivery platform helps software teams rapidly release code with confidence by automating the build, test, and deploy process. Offers a modern software development platform that lets teams ramp.

TeamCity

TeamCity

TeamCity is a user-friendly continuous integration (CI) server for professional developers, build engineers, and DevOps. It is trivial to setup and absolutely free for small teams and open source projects.

Drone.io

Drone.io

Drone is a hosted continuous integration service. It enables you to conveniently set up projects to automatically build, test, and deploy as you make changes to your code. Drone integrates seamlessly with Github, Bitbucket and Google Code as well as third party services such as Heroku, Dotcloud, Google AppEngine and more.

wercker

wercker

Wercker is a CI/CD developer automation platform designed for Microservices & Container Architecture.

GoCD

GoCD

GoCD is an open source continuous delivery server created by ThoughtWorks. GoCD offers business a first-class build and deployment engine for complete control and visibility.

Shippable

Shippable

Shippable is a SaaS platform that lets you easily add Continuous Integration/Deployment to your Github and BitBucket repositories. It is lightweight, super simple to setup, and runs your builds and tests faster than any other service.

Buildkite

Buildkite

CI and build automation tool that combines the power of your own build infrastructure with the convenience of a managed, centralized web UI. Used by Shopify, Basecamp, Digital Ocean, Venmo, Cochlear, Bugsnag and more.

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