Worse in some ways, better in others. DuckDB is often an excellent tool for this kind of task. Since it can run parallelized reads I imagine it's often faster than command line tool, and with easier to understand syntax
IMHO the main point of the article is that typical unix command pipeline pipeline IS parallelized already.
The bottleneck in the example was maxing out disk IO, which I don't think duckdb can help with.
More importantly, you have your data in a structured format that can be easily inspected at any stage of the pipeline using a familiar tool: SQL.
I've been using this pattern (scripts or code that execute commands against DuckDB) to process data more recently, and the ability to do deep investigations on the data as you're designing the pipeline (or when things go wrong) is very useful. Doing it with a code-based solution (read data into objects in memory) is much more challenging to view the data. Debugging tools to inspect the objects on the heap is painful compared to being able to JOIN/WHERE/GROUP BY your data.