Updated June 12, 2023
Introduction to Airflow vs Jenkins
Airflow is defined as a management platform which is an open-source workflow that was started and created by Airnib and is now the part of Apache and therefore Airflow which is used in creating workflows which are in Python programming language which can be easily scheduled and monitored via interfaces provided by Airflow which are built-in. Jenkins is also defined as an automation server that is being used for automating the software development parts that are related to testing, building, and deploying and hence therefore Jenkins support facilitating continuous delivery and continuous integration and Jenkins can be run in Apache Tomcat which is a servlet container.
Head to Head Comparison Between Airflow vs Jenkins (Infographics)
Below are the top 8 differences between Airflow vs Jenkins:
Key Differences of Airflow vs Jenkins
Let us see some key differences :
Apache Airflow is mainly used to maintain and author a data pipeline which is workflow automation for scheduling such data pipelines and these Airflows use these workflows which are used in acyclic graphs such as DAGs of tasks which provides easier maintenance, testing, etc. Whereas, Jenkins is mainly used for continuous integration and continuous deliveries in any software deployment, testing, building, etc of any software parts. Hence Jenkins is used to lowering the code repetition along with effortless auditing.
- Supporting Features
Apache Airflow supports few important features such as backfilling which help to run any tasks with specified timings that are framed by the users which gives the users freedom to backfill the entire DAG so that the users can reprocess historical data after the new feature addition for coping with data loss, Airflow also supports concurrency for managing concurrent tasks and also supports Xcom feature which helps to have cross-communication techniques easily between tasks, Whereas Jenkins also provides various features as it also supports execution of concurrent tasks only when the job configuration is checked else it supports parallel execution of tasks, it also supports a feature where it can distribute work throughout multiple machines so that it can easily drive for easy testing, building and deploying and it also provides multiple use cases such as GitHub, Java, PHP, etc.
- Better reviews of the users
Apache Airflow is sensible to use when you are dealing with ETL job performances where these Airflows help to restart at any point during such ETL process and hence it is said that Airflow is not any library and therefore it needs to be deployed and this makes less sense on small ETL jobs. Whereas Jenkins, are mostly recommended for bigger projects where these projects need a huge number of built-in plug-in where users need not have any more customizations as the users have the capability to change anything or everything though even the process is running to start this process it will take few minutes and the quick start may not be easily supported by this CI Jenkins.
Comparison Table of Airflow vs Jenkins
Below are a few comparisons mentioned :
|1||Airflow is an open-source platform to monitor and schedule data pipelines using programming languages such as Python.||Jenkins is also an open-source platform and is known as server-based systems which support software development using continuous integrations and continuous deliveries with more than 300 plus built-in plug-in.|
|2||Apache Airflow provides a few lists of integrations such as Apache Druid, Soda, Databand, MaxPatrol, Azure Purview, etc.||Jenkins also provides with a large number of integrations such as Device42, Lokalise, Qualibrate, WhiteSource, Zebrunner, GitHub, Wufoo, CloudQA, etc.|
|3||Apache Airflow has some categories which make Airflow good at these categories such as Data Pipelines, Workflow Automation, ETL, Automation, Workflow, etc.||Jenkins also has some categories which make Jenkins also popular and such categories are DevOps tools, continuous deployment, continuous integration, etc.
|4||As the part of DAG definition Airflow is provided with a feature of managing concurrent parallel tasks and these DAGs which are inside helps the scheduled runs which can be accessed and navigated very easily.||Jenkins also allows concurrent builds to be executed only if necessary and it allows parallel execution of builds for any tasks. The concurrent builds are executed only when the check box in the job configuration is checked.|
|5||Airflow is widely preferred when dealing with features such as updates on directions, roadmaps, etc by many different users than Jenkins. Therefore Apache Airflow is easy to use than Jenkins.||Jenkins is not much used when any users are dealing with easy access of scheduled runs with proper navigation. And hence Jenkins is a bit difficult to use when compared to Airflow.
|6||Airflow provides quality support to the users but users face a bit of difficulty in setting up and also when doing business with this Airflow||Jenkins also provides quality support for the users and unlike Airflow, it does provide ease in setting up and also ease in doing business with Jenkins when compared to Apache Airflow.|
|7||Apache Airflow is more for production scheduled tasks. As Apache Airflow is not a DevOps tool it’s a workflow orchestration tool.||Jenkins is more for CI/CD non-production tasks when compared to Apache Airflow.|
|8||Apache Airflow is supported on a platform such as SaaS. Therefore Apache is a server-based tool.|| Jenkins also is supported on platforms such as Windows and Mac. Therefore Jenkins is CI/CD-based tools in it.
In this article, we conclude that Apache airflow and Jenkins are both good and better in their own fields and different users use them based on their requirements. Therefore Jenkins is for more CI/CD tools for configuration or triggering any build or tests and other CD tasks also. Airflow is more for considering the production scheduled tasks and hence Airflows are widely used for monitoring and scheduling data pipelines whereas Jenkins are used for continuous integrations and deliveries.
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