datafusion is apache v2 licensed. [2]
pg_lakehouse built on top of data fusion is AGPL v3 + business licensed. [3]
[1] https://github.com/duckdb/duckdb/blob/main/LICENSE
[2] https://github.com/apache/datafusion/blob/main/LICENSE.txt
[3] https://github.com/paradedb/paradedb/blob/dev/LICENSE
Most companies won't touch AGPL v3 license. Maybe not a bad thing, but FYI.
At Google I was somehow allowed to use Emacs for development, but new copyleft software was immediately dismissed by legal, even if it's source was not getting into /google3 nor leaving my laptop.
https://raymii.org/s/blog/I_enforced_the_AGPL_on_my_code_her...
There are various explanations in plain english sometimes offered about how the AGPL will apply. None of these are true.
Companies that have a made a business decision to provide AGPL licensed code do so with the understanding that no serious business will ever consider using such a product in their software stack. If you choose an AGPL licensed product it will (rightly) become a gigantic headache at some point. It will certainly become a problem if anyone does due diligence.
Still, AGPL is a proper open-source license, unlike the sleazy fake ones adopted by Redis, Elastic or MongoDB.
In real world, I need a system which must be writing data into parquet files. If such system exist, why would I ever choose Postgres to query. I can pretty much use same data lakes/systems which are writing the data to query the data. If I want to scale horizontally, I would use something like duckdb for in-process or even simpler solutions instead of eating the transactional database process workers.
(And postgres sql DML writing to iceberg would be even better…)
Poking around, the Postgres/iceberg options recently were articulated here:
https://medium.com/datareply/unlocking-the-power-of-iceberg-...