Which feature enhances the performance of workloads in Oracle Autonomous Database?

Predictive resource scaling based on workload is a feature that significantly enhances the performance of workloads in Oracle Autonomous Database. This capability allows the database to automatically adjust its resources—such as CPU and I/O—based on the current workload demands. By utilizing machine learning, the system can anticipate resource needs and proactively allocate the necessary resources to ensure optimal performance. This dynamic approach means that as workloads increase or decrease, the database can adapt in real-time, leading to improved efficiency and reduced latency for users.

In contrast, static resource allocation does not provide the flexibility required for varying workloads, limiting performance in scenarios of fluctuating demand. Manual tuning of database parameters requires human intervention and can lead to performance bottlenecks if not adjusted properly, giving up the potential benefits of automation. Replication of data across multiple sites, while it enhances availability and disaster recovery capabilities, does not directly contribute to the performance optimization of individual workload executions within a single database. Hence, predictive resource scaling is a crucial feature that ensures the Autonomous Database can provide high performance consistently.