Apache Airflow® and Apache NiFi are two distinct open-source tools used to manage data, each catering to different needs within data management and workflow orchestration. Apache NiFi, originally developed by the NSA, excels in automating data flow between systems, making it ideal for handling large volumes of data through a user-friendly, drag-and-drop interface without requiring coding skills. It is particularly suited for long-running ETL processes and live batch streaming, despite its limitations in scaling and scheduling. In contrast, Apache Airflow® is a flexible task scheduler and data orchestrator favored for its robust capabilities in scheduling tasks, managing dependencies, and creating workflows as directed acyclic graphs (DAGs), written in Python. This makes it highly suitable for complex workflows and business-critical processes, supported by a vibrant community and a rich user interface. While Airflow is more widely adopted due to its versatility and active community, the choice between the two tools hinges on specific use cases: NiFi is optimal for basic big data ETL processes, whereas Airflow is the preferred option for orchestrating and executing sophisticated workflows.