toyed with pg_lake against our absolute dump of iceberg files (the nerds in my field call it a data lakehouse but engineering already has too many abstractions). it's pretty insane having postgres & the power of duckdb for mega aggregation, i threw a lot of wild windowed queries and aggregations at it and it seemed to really intuitively switch to using the duckdb jujutsu very well.

looking at migrating the rest of our catalog to iceberg now just to have the pg_lake option in our back pocket for future application development. it's so damn cool, as far as dbs go i haven't personally been involved in anything that needed more power than what postgres could deliver with writes. to be able to tack on bigboi analytics on top of it really consolidates a lot for us. im generally pretty cynical of these big saas peoples acquiring cool stuff but snowflake nabbing crunchydata here (crunchydata = guys who work on some pretty interesting postgres extensions) and helping them push this one to the a proverbial finish line and then open sourcing it was really great to see. i was worried when the acquisition went down because this was the major postgres thing i was really hoping someone would deliver, and crunchydata imo seemed to have the best plan outlined that understood the need.

it's faster than previous Postgres.

e.g. the gender_name example would already be optimized in duckdb via columnar execution and “aggregate first, join later” planning.

DuckDB and other specialized DBs benefit from much more optimized math, data structures and data storage/ memory lookups I'd assume.

But a 5x increase simply by optimizing the planner is nothing to be ashamed of.