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DuckDB vs the Modern Data Pile-Up
A practical look at how an embedded OLAP engine trims layers, cuts costs, and simplifies your analytics architecture.
Learn how DuckDB streamlines the modern data stack — reducing layers, speeding analytics, and simplifying architectures without spinning up heavy infrastructure.
You’ve probably seen the same slide a hundred times.
Boxes labeled ingest, transform, warehouse, lakehouse, semantic layer, BI, ML, each connected with arrows like a plate of data spaghetti.
And at some point, someone on the team quietly asks:
“Do we really need all of this just to count events by country?”
That’s where DuckDB starts to get interesting — not as a shiny new box, but as a way to remove some boxes entirely.
Let’s unpack how this little in-process database can genuinely simplify the modern data stack, not just add another moving part.
The Modern Data Stack Got… Heavy
The promise vs. reality
The “modern data stack” promised:
- EL pipelines into a cloud warehouse
- Transformations in SQL (dbt, etc.)
