You would use Dask over Polars when you need to handle very large datasets that exceed your local machine's memory or when you want to distribute the computation across a cluster of machines. For example, if you're analyzing a massive dataset stored in Parquet files across multiple servers and need to perform complex computations while leveraging parallel processing, Dask is a suitable choice.
Polars is best used when performance and memory efficiency are critical, especially with large datasets. For instance, in a scenario where you are processing a large parquet file for real-time analytics where speed is essential, Polars would be preferred over Dask due to its optimized performance.