What happens to optimizer hints and parallel hints by default in Autonomous Database?

In Autonomous Database, optimizer hints and parallel hints are ignored by default. This design choice aligns with the overarching goal of the Autonomous Database to automate database management processes and optimize performance without requiring manual intervention. The system relies on its automated optimization capabilities, which utilize machine learning algorithms and advanced analytics to determine the most efficient execution plans.

By ignoring hints, the Autonomous Database can dynamically adapt to changing data patterns and workloads, optimizing for performance without the constraints that manually specified hints might impose. This allows the database to make decisions based on the current state of the data and workload instead of potentially outdated or static hints.

The other options do not align with how the Autonomous Database is designed to operate. For instance, activating hints by default would contradict the automation philosophy of the service. Similarly, stating that hints have no effect on performance would be misleading, as they do not impact performance in this context because they are not considered. Lastly, requiring administrator approval for hints would also be contrary to the self-managing nature of the Autonomous Database, which aims to minimize the need for manual oversight.