DuckLake Tutorial Shows 10,000-Row DuckDB Lakehouse With Time Travel and Maintenance
Updated
Updated · KDnuggets · Nov 13
DuckLake Tutorial Shows 10,000-Row DuckDB Lakehouse With Time Travel and Maintenance
1 articles · Updated · KDnuggets · Nov 13
Summary
DuckLake’s new tutorial walks users through building a local lakehouse on DuckDB in under an hour, ending with a working 10,000-row setup backed by Parquet files and a SQL catalog.
DuckLake stores table metadata—schemas, snapshots and file statistics—in a SQL database while keeping data in Parquet, letting file discovery happen through SQL rather than metadata files.
The step-by-step guide loads 5,000 January rows, appends 5,000 February rows, updates records, evolves the schema, and queries older versions with AT (VERSION => n) to restore deleted data.
Maintenance is part of the workflow: ducklake_merge_adjacent_files compacts small files, while snapshot expiry and CHECKPOINT are needed later to reclaim storage because old files remain for time travel.
The tutorial also flags deployment limits and options: DuckLake 1.0, released in April 2026, needs DuckDB 1.5.2+, uses a single-client DuckDB catalog locally, and points multi-user setups to PostgreSQL.