From Laptop to Lakehouse: Analytical SQL with DuckDB

TL;DR: DuckDB is a complete analytical SQL engine that runs in-process. No server, no dependencies, one binary, MIT licensed. This session is one duck and a lot of live demos.

While the big data warehouses were busy adding pricing tiers, a small open source project from a research group in Amsterdam quietly built one of the fastest analytical engines around. No license fees, no vendor lock-in, no sales call required.

What makes DuckDB remarkable is how far the same engine scales. It starts as a CLI tool on your laptop, poking at CSV, JSON and Excel files with a friendly SQL dialect and larger-than-memory processing that spills to disk instead of falling over. The same binary embeds into your Java application via JDBC and runs analytics in-process, with no network hop in sight. Point it at S3 and it queries files in place; add DuckLake and it becomes a full lakehouse on open formats. And with the new Quack protocol, ducks are learning to talk to each other, turning DuckDB into a client-server database with multiple writers.

Expect live demos along that entire scale, from laptop to lakehouse.
You will leave with a good sense of what DuckDB can do for you, where its limits are, and why it keeps showing up in so many stacks.

Who is this for? Developers, architects and data-curious engineers who occasionally need answers from data but would rather not operate a warehouse to get them. SQL basics are enough; no data engineering background required.