Partitioning is only needed when the dataset size exceeds a specific threshold, and it can improve performance by reducing the storage costs.

Partitioning is always necessary, regardless of the dataset size, as it can significantly improve query performance.

Partitioning is needed when the dataset has a natural partition key, such as date or time, and it can improve performance by reducing the amount of data scanned during queries.

Partitioning is not needed in Azure Data Lake Storage Gen2, as the storage service automatically optimizes performance.