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.
The article discusses streaming patterns in DuckDB, highlighting its capabilities for handling large-scale data processing efficiently. It presents various approaches and techniques for optimizing data streaming and querying, emphasizing the importance of performance and scalability in modern data applications.