1 link tagged with all of: data engineering + polars + benchmarking + duckdb
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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.
- DuckDB handled the 1TB benchmark successfully while Polars crashed with out-of-memory errors
- DuckDB's memory management and execution engine scale more effectively to large datasets than Polars'
- Polars is optimized more for in-memory, smaller-scale workloads and breaks down at larger scales like 1TB