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Apache Airflow Evaluation Guide: Pros and Cons of Airflow DAG vs Declarative Data Pipelines
Is Airflow right for your next big data project? Read our guide to find out.
Apache Airflow is a powerful and widely-used open-source workflow management system (WMS) designed to programmatically author, schedule, orchestrate, and monitor data pipelines and workflows. Airflow enables you to manage your data pipelines by authoring workflows as Directed Acyclic Graphs (DAGs) of tasks.
Download our free white paper to learn:
- Overview of orchestration via DAGs in Airflow
- Ideal use cases and advantages of Airflow
- Cons and challenges when using Airflow
- An alternative approach based on declarative data pipelines
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Who should read this guide?
- Data architects and engineering leaders looking to optimise their data architecture and build a modern data stack
- Data engineers who want to build more efficient orchestration in their data transformation flows
- Data scientists who need self-service access semi-structured data from cloud storage using SQL
