In late 2023, the Java community started a challenge to find the most efficient way to process a file with 1 billion rows of data. Unsurprisingly, many database communities quickly took on the same challenge with varying results. Postgres, in many cases, performed the worst without close attention to settings and efficient resource utilization. But, with a little more effort, could it compete head-to-head?

In this session, we’ll look at the original challenge and how to approach it with vanilla Postgres beyond the basics. Next, we’ll explore how the increasingly popular in-memory analytics database, DuckDB, handles the same challenge. Finally, we’ll explore recent opportunities to integrate the two databases together to provide a powerful analytical engine with Postgres for the best of both worlds.