Performance comparison measuring aggregation throughput, memory efficiency, and vectorized query speeds across Pandas, Polars, and DuckDB on 1M+ rows.
| Engine | Query Execution (ms) | Speedup vs Baseline |
|---|---|---|
| Pandas | ~140 - 200 ms | 1.0x (Baseline) |
| Polars | ~15 - 30 ms | 6x - 10x faster |
| DuckDB | ~10 - 25 ms | 8x - 15x faster |
git clone [https://github.com/AhmadBilalDSA/data-engine-benchmarks.git](https://github.com/AhmadBilalDSA/data-engine-benchmarks.git)
cd data-engine-benchmarks
pip install pandas polars duckdb numpy
python benchmark.py# data-engine-benchmarks