> So is the magic here that it's Postgres? What makes being able to query something in Postgres special?

There are a bunch of pros and cons to using Postgres vs. DuckDB. The basic difference is OLTP vs. OLAP. It seems pg_lake aims to give you the best of both. You can combine analytics queries with transactional queries.

pg_lake also stores and manages the Iceberg catalog. If you use DuckDB you'll need to have an external catalog to get the same guarantees.

I think if you're someone who was happy using Postgres, but had to explore alternatives like DuckDB because Postgres couldn't meet your OLAP needs, a solution like pg_lake would make your life a lot simpler. Instead of deploying a whole new OLAP system, you basically just install this extension and create the tables you want OLAP performance from with `create table ... using iceberg`

> when we say it’s now queryable by Postgres, does this mean that it takes that data and stores it in your PG db?

Postgres basically stores pointers to the data in S3. These pointers are in the Iceberg catalog that pg_lake manages. The tables managed by pg_lake are special tables defined with `create table ... using iceberg` which stores the data in Iceberg/Parquet files on S3 and executes queries partially with the DuckDB engine and partially with the Postgres engine.

It looks like there is good support for copying between the Iceberg/DuckDB/Parquet world and the traditional Postgres world.

> Or it remains in S3 and this is a translation layer for querying with PG?

Yes I think that's right -- things stay in S3 and there is a translation layer so Postgres can use DuckDB to interact with the Iceberg tables on S3. If you're updating a table created with `create table ... using iceberg`, I think all the data remains in S3 and is stored in Parquet files, safely/transactionally managed via the Iceberg format.

https://github.com/Snowflake-Labs/pg_lake/blob/main/docs/ice...