DuckDB has proven to be superior to Polars when handling large datasets, particularly 1TB of data. While DuckDB effectively manages memory and execution with a robust design, Polars struggles with large data processing, leading to out-of-memory errors.

Polars, a DataFrame library designed for performance, has introduced GPU execution capabilities that can achieve up to a 70% speed increase compared to its CPU execution. This enhancement is particularly beneficial for data processing tasks, making it a powerful tool for data engineers and analysts looking to optimize their workflows.

The article provides an honest review of Polars Cloud, focusing on its performance and usability for data engineering tasks. It highlights the advantages and disadvantages of the platform, comparing it with other solutions in the market. The review aims to give potential users insight into whether Polars Cloud is a suitable choice for their data processing needs.