Pipeline Orchestration: Airflow, Prefect, Dagster
Orchestrate data pipelines with Airflow DAGs, Prefect flows, or Dagster jobs. Compare scheduling, retry logic, observability, and local development.
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Tags: etl, orchestration, data-engineering
Pipeline Orchestration: Airflow, Prefect, and Dagster for Data Workflows Orchestration is the layer that decides when pipelines run, in what order, with what dependencies, and what to do when something fails. Without it, you have a collection of scripts that someone runs manually — and when the ingestion job runs before the transformation job and produces garbage, nobody knows why. This guide covers the three leading orchestrators — Airflow, Prefect, and Dagster — with an honest assessment of each. --- What Orchestration Actually Does Before comparing tools, be clear on what you need: Scheduling — Run this pipeline at 2am every day Dependency management — Run transformation only after ingestion succeeds Retry logic — Retry failed tasks 3 times before alerting Observability — Show which…
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