Dagster is ideal when building complex data pipelines that require modularity, scalability, and testing. It is particularly useful when dealing with numerous data sources and needing to ensure data quality throughout the process. For example, if you need to orchestrate a data pipeline that pulls data from multiple APIs, transforms it, and loads it into a data warehouse, Dagster's features can help manage the complexity more effectively than Oozie's traditional job orchestration.
Apache Oozie is particularly useful in environments heavily reliant on the Hadoop stack, as it is designed to manage complex workflows of Hadoop jobs. For example, if you have a series of MapReduce, Hive, and Pig jobs that need to be executed in a specific order within a Hadoop cluster, Oozie would effectively manage these dependencies and execution flow, making it a suitable choice for such scenarios.