Comparison
External tablevsLakehouse
External table
the warehouse queries files it does not own, so dropping the table leaves the data exactly where it was.
A table definition in a query engine pointing at data stored and managed elsewhere. It is how a warehouse reads a lake without ingesting it, and how the same files can be shared between engines. The trade is that the engine cannot make guarantees about data it does not control: statistics go stale, files can change under a running query, and nothing stops another process writing something the schema does not describe.
Full entry →Lakehouse
the tables are open files in a bucket and you still get transactions, schema enforcement and a rollback.
A table format layered over object storage so that a lake behaves like a warehouse: atomic commits, snapshot isolation, schema enforcement and time travel over plain Parquet files. It exists because the two-system arrangement — lake for raw, warehouse for modelled — meant every table was copied, and the copy was the thing that drifted. The remaining trade is maturity: the metadata layer is now a component you operate, and small-file and compaction management is your job rather than the vendor's.
Full entry →