Dagster vs. Airflow

When Airflow was originally designed in 2014, it was a huge step forward. But data engineering has progressed dramatically since then. Dagster was built from the ground up to equip data teams with the right tools for building and managing a data platform in today’s data ecosystem.

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Why data teams are switching from Airflow to Dagster

Asset-centric development

Dagster’s Software Defined Assets provide an intuitive framework for collaboration across the enterprise. You can focus on delivering critical data assets, not on the tasks of pipelines.

Airflow is task-centric and does not provide asset-aware features or a coherent Python API. It is typically implemented after pipelines have been designed to trigger the required tasks.

Better testing and debugging

Dagster is designed for use at every stage of the data development lifecycle. It facilitates local development, unit testing, CI, code review, staging, and debugging.

Airflow pipelines are harder to test and review outside of production deployments. Many teams working on Airflow end up doing their final testing in production.

Cloud-native infrastructure

Dagster is cloud- and container-native, and designed for today's data infrastructure (ECS, K8s, Docker). Dependencies are easy to manage and upgrades are smooth. Dagster+ provides a turnkey hosting solution.

Isolating dependencies and provisioning infrastructure with Airflow is complex and time consuming.

“Airflow was built to string tasks together, not provide an overview of all the ways data is flowing or what’s causing issues.”

David Jayatillake

Going with the Airflow

Migrating off Airflow is now a breeze

Dagster provides tooling that makes porting Airflow DAGs to Dagster much easier. Data teams looking for a radically better developer experience can now easily transition away from legacy imperative approaches and adopt a modern declarative framework that provides excellent developer ergonomics.

Find out how

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Every Dagster+ trial includes:

Unlimited code locations

Use Dagster code locations to support different projects and multiple teams all within one data platform

Unlimited branch deployments

A temporary deployment built for testing purposes that spins down when a branch is merged

Serverless or Hybrid

Choose between a fully managed Serveless offering or a Hybrid deployment.

Authentication & SSO

Event logging

Unlimited alerts

Automatically trigger Slack or email notifications on events like job failures, sensor failures, or and agent downtime.

Data quality checksLearn more

Insights (Operational observability)Learn more

Embedded ELTLearn more

Declarative asset schedulingLearn more

dbt-native orchestrationLearn more

Easily migrate & run existing Airflow DAGsLearn more

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Ramp up quickly

We offer many resources to get started, including the free trial with starter templates, an active and growing community on Slack, and detailed docs with AI assistant and tutorials.

A great place to start is with our free Dagster University course content.

Check out Dagster University.

Dagster+ for Enterprise

Looking for unlimited deployments, advanced RBAC and SAML-based SSO, all on a SOC2 certified platform? Contact the Dagster Labs sales team today to discuss your requirements.

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