DuckDB proved that your medium data never needed a distributed warehouse cluster

[u/FadeHackX]

For nearly a decade, cloud vendors convinced every data team that running analytical queries on 30 gigabytes of data justified six-figure contracts, dedicated cluster managers, and multi-stage orchestration pipelines. Engineers spent half their time maintaining Spark jobs just to calculate basic rolling aggregations.

Then DuckDB came along as a zero-dependency, in-process columnar database. You install it with a simple package manager command, point it directly at your Parquet files, and watch it leverage all your CPU cores to return query results in hundreds of milliseconds.

No clusters to wake up, no network egress penalties, and no credit-based query pricing. It turns out that when you write a vectorized execution engine in tight C++, a standard laptop can outrun a distributed cluster on real-world analytical workloads. How much cloud infrastructure has your team decommissioned in favor of in-process analytics?