About Data Refresh Performance

Oracle strives constantly to improve performance for data loading in pipelines.

The performance of loading data for your instance will vary. The time to complete data processing, both full warehouse loads and incremental data loads, depends on various factors. A data pipeline load includes the following:

  • Extracting the data from the Oracle Fusion Cloud Applications.
  • Loading the data into Oracle Autonomous Data Warehouse.
  • Transforming the data into the prebuilt schema.
The time to complete each of these steps is determined by various factors including:
  • The availability of the source system.
  • The size and complexity of the source data.
  • The activated functional areas.
  • Custom SQL queries that impact Oracle Autonomous Data Warehouse.
  • Your queries running concurrently.
  • Customizations made on the source system objects (which require a full load for those objects).
  • The patching of source and target systems.

Data refresh is typically completed daily unless the data pipeline jobs are turned off or stuck. You can observe data loading times for your specific source and warehouse configuration to estimate the time it takes for an incremental daily refresh and for a full warehouse load. This information can help you plan for the optimal time in the day to start your daily data refresh. You may want to schedule the data load to run during off-peak hours, for example, run initial full warehouse loads during weekends and incremental loads during weeknights to ensure that users aren't impacted.


You can view the estimated refresh completion time for daily pipelines on the Pipeline Settings page in the Estimated Refresh Completion field as a Preview feature. This enables you to plan your tasks in the application.
Estimated Refresh Completion details on the Pipeline Parameters page