More integrations are great. Anyway, the "this is awesome" moment (for me) will be when you could mix row- and column-oriented tables in Postgres, a bit like Timescale but native Postgres and well done. Hopefully one day.

I want MPP HTAP where SQL inserts/COPYs store data in three(!) formats: - row-based (low latency insert, fast row-based indexed query for single-row OLTP) - columnar-based (slow inserts/updates, fast aggregates/projections) - iceberg-columnar-based (better OLAP price/performance and less lockin than native columnar) And for SELECTs the query engine picks which storage engine satisfies the query using some SQL extension like DB2 "WAITFORDATA" or TiDB @@tidb_read_staleness or MemSQL columnstore_latency and/or similar signalling for performance-vs-cost preference.

And a common permissioning/datasharing layer so I can share data to external and internal parties who can in turn bring their own compute to make their own latency choices.

Hypertables definitely had the arrays columns auto-expanding with the custom node type. Not sure what else it would look like for what you describe.

That said, don't sleep on the "this is awesome" parts in this project... my personal favorite is the automatic schema detection:

``` CREATE TABLE my_iceberg_table () USING iceberg WITH (definition_from = 's3://bucket/source_data.parquet'); ```