Curious to learn more about how people are using it?

Are they downloading parquet files and running analyses locally, or are they connecting to Iceberg-like data lake and leveraging DuckDBs query engine capabilities or have you exposed an interface (REST, UI) to query your data?

I've got a couple of different use cases:

- ETL pipelines running on K8s nodes. Using their streaming processing engine means I can run smaller pods/nodes if needed, for datasets that may have required large dataframe-like transformations that may have buffered a big dataset into memory previously.

- A CLI distributed to an internal team to do a postprocessing step on a large modeling dataset - to get it into a consumable format and upload it to a bucket as a .db file.

- A SvelteKit app that used the node duckdb bindings to attach to the .db on the bucket and explore the results through a suite of BI tools. These tables have millions of rows, and would be pretty heavy to store in PG. The DuckDB version works really, really well.

We use DuckDB WASM with parquet to build dashboards in-browser. It's cool to be able to write SQL directly in a browser and not have to rely on REST/Graphql/etc to access the data layer.

We use WASM DuckDB as the target for an in-browser agentic feature. Generated SQL runs against the user's individual tables that then feed in-browser dashboards.

Excellent performance.