Here is a 1-paragraph summary of the text: The authors demonstrate a significant speedup when using the Arrow library with dlt to load data from a PostgreSQL database, achieving ~30x faster performance compared to SQLAlchemy. The speedup is mainly due to the fact that the data is already structured in the source, allowing for efficient inference and validation of the schema during loading. In contrast, the classical approach with SQLAlchemy requires row-by-row processing, which leads to slower performance. The authors attribute the speedup to the zero-copy extraction feature of Arrow and the ability to load data from local databases without network roundtrips, making it an attractive alternative for data engineering tasks.