For optimal performance, what type of storage is recommended for Oracle Data Flow?

Oracle Data Flow is designed to process large amounts of data efficiently, and utilizing object storage aligns well with these requirements. Object storage systems are highly scalable, allowing users to store vast amounts of unstructured data without running into limitations that other storage systems may impose.

In the context of big data and analytics, object storage provides several advantages: it supports high-throughput access patterns, making it ideal for workloads that read and write large datasets. Additionally, object storage is designed to handle variable data formats and is accessible over HTTP, which enhances its flexibility for cloud-based applications.

Furthermore, object storage typically offers durability and redundancy, ensuring long-term data integrity and availability. This is particularly important for data processing workflows like those in Oracle Data Flow where data accessibility and reliability are critical for maintaining performance.

Overall, the nature of object storage makes it a superior choice for workloads requiring efficiency, scalability, and high availability, which is why it is recommended for optimal performance in Oracle Data Flow.