Automatic Ordering: Complicated data pipelines are comprised of a large number of small, simple processing steps. Without DBgen, the user must make sure that the ETL steps are run in the correct order. If one ETL step needs to query a given column in the database, the ETL step that populates that column needs to be run first. This process is laborious, especially in the case of scientific research, where frequent changes to the data pipeline are expected. DBgen automatically determines the correct order to run the ETL steps by using the structured information in each Generator object to create a directed acyclic graph (DAG). This feature is significant because it allows the user to not think about the whole data pipeline when adding or editing an ETL step, even if the change completely disrupts the dependencies among the ETL steps. This feature contributes to the reconfigurability and maintainability of DBgen ETL pipelines. Furthermore, this computational graph can be visualized to show the full flow of data from its source, through all processing steps, to the final destination in the database. This adds transparency to all DBgen ETL pipelines.