DuckLake can do things that pg_lake cannot do with Iceberg, and DuckDB can do things Postgres absolutely can't (e.g. query data frames). On the other hand, Postgres can do a lot of things that DuckDB cannot do. For instance, it can handle >100k single row inserts/sec.
Transactions don't come for free. Embedding the engine in the catalog rather than the catalog in the engine enables transactions across analytical and operational tables. That way you can do a very high rate of writes in a heap table, and transactionally move data into an Iceberg table.
Postgres also has a more natural persistence & continuous processing story, so you can set up pg_cron jobs and use PL/pgSQL (with heap tables for bookkeeping) to do orchestration.
There's also the interoperability aspect of Iceberg being supported by other query engines.
For some reason people more easily understand the limits of CPU and memory, but overlook disk constantly.