I went through this trade off at my last job. I started off migrating my adhoc queries to duckdb directly from delta tables. Over time, I used duckdb enough to do some performance tuning. I found that migrating from Delta to duckdb's native file format provided substantial speed wins.
The author focuses on read/write performance on Delta (makes sense for the scope of the comparison). I think if an engineer is considering switching from spark to duckdb/polars for their data warehouse, they would likely be open to data formats other than Delta, which is tightly coupled to the spark (and even more so to the closed-source Databricks implementation). In my use case, we saw enough speed wins and cost savings that it made sense to fully migrate our data warehouse to a self managed duckdb warehouse using duckdb's native file format.
The author focuses on read/write performance on Delta (makes sense for the scope of the comparison). I think if an engineer is considering switching from spark to duckdb/polars for their data warehouse, they would likely be open to data formats other than Delta, which is tightly coupled to the spark (and even more so to the closed-source Databricks implementation). In my use case, we saw enough speed wins and cost savings that it made sense to fully migrate our data warehouse to a self managed duckdb warehouse using duckdb's native file format.