The Duck and the DataFrame: A Data Engineer’s Journey with DuckDB - Ankur Jain (PyCon AU 2025) @PyConAU
The Duck and the DataFrame: A Data Engineer’s Journey with DuckDB - Ankur Jain (PyCon AU 2025)  @PyConAU
Uploaded September 2025 | Updated September 2026, 5 hours ago
(Ankur Jain) I’ve used pandas for years, but as my data grew, my local workflows started to slow down. Joins got sluggish, memory errors showed up, and simple tasks became harder to manage. That’s when I found DuckDB, a fast, in-process SQL engine that brought the speed and flexibility I was missing.

This talk isn’t about replacing pandas. It’s about knowing when to reach for something different. I’ll share how DuckDB helped streamline my workflow, with real examples, side-by-side comparisons, and a quick intro to DuckLake, a SQL-based Lakehouse format that fits naturally into modern Python analytics.

pretalx.com/pycon-au-2025/talk/3JMK73

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Fri Sep 12 10:00:00 2025 at Ballroom 1
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"The Duck and the DataFrame: A Data Engineer’s Journey with DuckDB" - Ankur Jain (PyCon AU 2025)

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