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What is a DAG?
It stands for a Directed Acyclic Graph and is the basis of Airflow, Prefect, and Dagster.
Lately I’ve spent a lot of time researching different orchestration tools to use within a data stack that I’m building at. I’ve been looking at Airflow, Dagster, and Prefect to name a few.
As someone who has never used one of these tools before, it was a bit confusing reading through documentation. I mean how many times are they going to mention DAG without actually explaining what DAG means!?
As a self-taught programmer who has learned most of what she knows on the job and through various tutorials and articles online, I needed to dive deep into what these tools meant when they referred to DAG. If you’re in the same boat as I was, hopefully this helps you out.
DAG stands for Directed Acyclic Graph. This is a concept often used in mathematics and computer science. It is basically a graph with arrows pointing from one event to another, forming a cycle that never really closes.
A DAG is a way of defining relationships and dependencies between different events. It shows you the order in which they have to be executed and which events depend on one another.
