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  1. Stackups
  2. Utilities
  3. Task Scheduling
  4. Workflow Manager
  5. Airflow vs OTRS

Airflow vs OTRS

OverviewDecisionsComparisonAlternatives

Overview

Airflow
Airflow
Stacks1.7K
Followers2.8K
Votes128
OTRS
OTRS
Stacks22
Followers44
Votes0
GitHub Stars858
Forks451

Airflow vs OTRS: What are the differences?

What is Airflow? A platform to programmaticaly author, schedule and monitor data pipelines, by Airbnb. 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.

What is OTRS? A customizable support desk software that manages workflows and structures communication. It is a modern, flexible ticket and process management system that allows service management professionals in any industry to keep pace with today’s lightning-fast,results-driven business environment.

Airflow and OTRS can be categorized as "Workflow Manager" tools.

Some of the features offered by Airflow are:

  • 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.

On the other hand, OTRS provides the following key features:

  • Help Desk Ticket Creation
  • Self-Service Tools
  • Dashboard with Filter Options

Airflow and OTRS are both open source tools. It seems that Airflow with 14.3K GitHub stars and 5.36K forks on GitHub has more adoption than OTRS with 620 GitHub stars and 398 GitHub forks.

Airbnb, Slack, and 9GAG are some of the popular companies that use Airflow, whereas OTRS is used by GameDuell, FranceConnect, and Sicoob Credija. Airflow has a broader approval, being mentioned in 113 company stacks & 193 developers stacks; compared to OTRS, which is listed in 3 company stacks and 3 developer stacks.

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Advice on Airflow, OTRS

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
OTRS
OTRS

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 is a modern, flexible ticket and process management system that allows service management professionals in any industry to keep pace with today’s lightning-fast,results-driven business environment.

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.
Help Desk Ticket Creation; Self-Service Tools; Dashboard with Filter Options; SMS Notification System; SLA Management; Ticket Management; ITIL Processes; 3rd Party Integration.
Statistics
GitHub Stars
-
GitHub Stars
858
GitHub Forks
-
GitHub Forks
451
Stacks
1.7K
Stacks
22
Followers
2.8K
Followers
44
Votes
128
Votes
0
Pros & Cons
Pros
  • 53
    Features
  • 14
    Task Dependency Management
  • 12
    Cluster of workers
  • 12
    Beautiful UI
  • 10
    Extensibility
Cons
  • 2
    Observability is not great when the DAGs exceed 250
  • 2
    Open source - provides minimum or no support
  • 2
    Running it on kubernetes cluster relatively complex
  • 1
    Logical separation of DAGs is not straight forward
No community feedback yet
Integrations
No integrations available
Jira
Jira
JavaScript
JavaScript
Perl
Perl

What are some alternatives to Airflow, OTRS?

Jira

Jira

Jira's secret sauce is the way it simplifies the complexities of software development into manageable units of work. Jira comes out-of-the-box with everything agile teams need to ship value to customers faster.

GitHub Actions

GitHub Actions

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.

Apache Beam

Apache Beam

It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.

Bugify

Bugify

Bugify offers a simple way of managing issues for your projects.

Zenaton

Zenaton

Developer framework to orchestrate multiple services and APIs into your software application using logic triggered by events and time. Build ETL processes, A/B testing, real-time alerts and personalized user experiences with custom logic.

Luigi

Luigi

It is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.

ZenTao

ZenTao

You can effortlessly stay on top of your product development, create and delegate tasks, test your software, customize, store and secure your documents and more.

Bugzilla

Bugzilla

Bugzilla is a "Defect Tracking System" or "Bug-Tracking System". Defect Tracking Systems allow individual or groups of developers to keep track of outstanding bugs in their product effectively. Most commercial defect-tracking software vendors charge enormous licensing fees. Despite being "free", Bugzilla has many features its expensive counterparts lack.

Unito

Unito

Build and map powerful workflows across tools to save your team time. No coding required. Create rules to define what information flows between each of your tools, in minutes.

VersionOne

VersionOne

It is a formidable Agile management solution that is both comprehensive and versatile and developed for teams and projects of various scope and size. It is a compact platform that delivers outstanding performance in terms of managing and tracking multiple teams, tasks, and projects.

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