Moving past Airflow: Why Dagster is the Next-generation Data Orchestrator

Dagster is a next-generation data orchestrator that aims to address the limitations of traditional workflow engines like Airflow. It provides a holistic view of the data life cycle, offering improved development and testing experiences, orchestration environments, consumer-grade operations monitoring, and asset tracking capabilities. Dagster's functional data processing confers advantages such as testability, subset execution, data dependencies, built-in marshaling, typing, separation of I/O and compute, lightweight, schedule-less, ad hoc execution, process isolation, flexible distributed task scheduling, and structured event logging. It is designed to be a productivity environment for building and testing data applications in Python, growing with users from single-player mode on laptops to enterprise-grade platforms, and serving as an observability tool that provides consumer-grade tools supporting self-service operations, fast debugging, and asset tracking.

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