Airflow vs Unito
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. | 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. |
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. | Deep integrations between tools; Syncing that truly goes both ways; Design your dream workflows; Report and align on projects |
Statistics | |
Stacks 1.7K | Stacks 15 |
Followers 2.8K | Followers 31 |
Votes 128 | Votes 7 |
Pros & Cons | |
Pros
Cons
| Pros
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Integrations | |
| No integrations available | |
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