Airflow Migration Event
dagster-airflow library makes it much easier to switch from Airflow to Dagster. For teams looking for an alternative to Apache Airflow, this series of videos provides a tutorial and perspectives on how to successfully migrate.
Hear from data practitioners and Dagster implementation partners, as we discuss the best ways to make this transition.
The biggest challenges facing data teams
Nick Schrock, Founder and CTO at Elementl, explains the fundamental challenge for data teams: they are mission-critical to the organization yet face deep challenges related to managing their data platforms and achieving high levels of productivity.
Comparing Apache Airflow and Dagster
Data engineers are looking to get past the limitations of Airflow, the incumbent in the data orchestration layer. Dagster proposes a new paradigm centered on Assets and tools to support a full development lifecycle that radically boosts the productivity of data teams.
Tooling that makes migrating off Apache Airflow much easier
Pete Hunt, CEO of Elementl, on how the new dagster-airflow library significantly reduces the cost of migrating off Airflow and onto Dagster.
Migrate Apache Airflow DAGs to Dagster Jobs
Odette Harary, developer advocate at Elementl, shares details on how to successfully convert Airflow Ops to Dagster Jobs.
Migrate Apache Airflow DAGs to Dagster Software-defined Assets
Tim Castillo, developer advocate at Elementl, demonstrates how to migrate from Apache Airflow DAGs to Dagster Software-defined Assets.
Key considerations when planning your migration
Joe Van Drunen, software engineer at Elementl and author of the dagster-airflow library, shares some key considerations when planning your migration off Apache Airflow and onto Dagster.
How Group 1001 migrated off Apache Airflow and onto Dagster
Group 1001 migrated 73 Apache Airflow DAGs in 2 weeks with just 2 data engineers. Hear from Gu Xie, Head of Data Engineering, who led the effort.
whatnot embraces declarative orchestration
Stephen Bailey led whatnot’s migration from Airflow to Dagster. Starting with 50 Airflow DAGs running on mostly-daily cadences, the team now runs one hundred thousand individual Dagster jobs a month on myriad schedules.
The business benefits of Dagster over Airflow
INFOSTRUX helps clients select and implement the best possible technology to meet their business goals. Nasko Grozdanov explains the business benefits of using Dagster vs. Apache Airflow.
A feature comparison of Dagster vs. Airflow
Ritesh Kerwell on how specific Dagster features boosts the productivity of data engineering teams.