Which of the following is NOT a benefit of data partitioning in AWS?

Data partitioning is a technique that involves dividing a dataset into smaller, more manageable segments. This approach offers several advantages that enhance data processing and querying efficiency.

One of the primary benefits is improved performance, as partitioning allows systems to read only the relevant subsets of data rather than processing the entire dataset. This selective reading significantly accelerates data access. Independent scanning of data segments is another advantage because it enables parallel processing, wherein multiple segments can be scanned simultaneously, further enhancing overall performance.

Additionally, partitioning leads to faster query execution, as queries can be executed on smaller, focused segments of data, reducing the amount of data that needs to be processed for a given operation.

In contrast, increased security is not inherently a benefit of data partitioning. While partitioning may help organize and manage data, it does not directly enhance security measures. Security is typically addressed through other mechanisms, such as encryption, access control policies, and robust authentication protocols. Thus, the specific focus of the question on benefits associated with data partitioning leads to the conclusion that increased security does not fit into the typical advantages observed with this practice in AWS.