Airflow vs Shipyard
Overview
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CLI (Node.js)
Manual
Detailed Comparison
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. | na |
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. | - |
Statistics | |
Stacks 1.7K | Stacks 3 |
Followers 2.8K | Followers 4 |
Votes 128 | Votes 5 |
Pros & Cons | |
Pros
Cons
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What are some alternatives to Airflow, Shipyard?
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Zenaton
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Luigi
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Unito
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Vison AI
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Flumio
Flumio is a modern automation platform that lets you build powerful workflows with a simple drag-and-drop interface. It combines the power of custom development with the speed of a no-code/low-code tool. Developers can still embed custom logic directly into workflows.
PromptX
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iLeap
ILeap is a low-code app development platform to build custom apps and automate workflows visually, helping you speed up digital transformation.
Page d'accueil
Thaink² Analytics, la plateforme data et IA de nouvelles génération pour gérer vos projets de bout-en-bout. Fini les pipelines de données instables, les modèles ML/IA qui restent au stade du POC.
