Once you have developed a spark data pipeline using prophecy, you will want to schedule it to run at some frequency. To support this, Prophecy provides you with an easy to use low-code interface to develop Jobs, using two different schedulers:
Databricks Jobs - for simpler data-pipeline use-cases, where you just orchestrate multiple data-pipelines to run together. Databricks Jobs is a recommended scheduler, if you're Databricks Native.
Airflow - for more complex use-cases, where you have to use various operators, or need any additional data pre- / post-processing.
Alternatively, since Prophecy provides you native Spark code no GIT, you can easily integrate with any other scheduler. Read more about it here.