The useful part is that duckdb is so easy to use as a client with an embedded server, because duckdb is a great client (+ a library).

Similar to how git can serve a repo from a simple http server with no git installed on that (git update-server-info).

The frozen part is what iceberg promised in the beginning, away from Hive's mutable metastore.

Point to a manifest file + parquet/orc & all you need to query it is S3 API calls (there is no metadata/table server, the server is the client).

> Creating and publishing a Frozen DuckLake with about 11 billion rows, stored in 4,030 S3-based Parquet files took about 22 minutes on my MacBook

Hard to pin down how much of it is CPU and how much is IO from s3, but doing something like HLL over all the columns + rows is pretty heavy on the CPU.