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sunzhousz

I am very disappointed to see the direction: It is moving from a "interesting attempt to recreate system software" to "building flashy but useless demo"

Everyone who knows a bit about databases knows the difference between execution models and what kind of optimization it brings.

zhou here :)

Moonlink was arguably one of the best ZeroETL(mirroring) solution, and there's a reason we built LTAP instead (not just because it's cool and we can do it)

To me, two big issues with CDC/mirroring are: 1. For ad-hoc querying, CDC is usually not there when you need them, and it is too expensive to maintain for all tables if you don't query them often. 2. For true data pipeline, a simple mirror is not enough, you will end up building all kinds of transformation and it essentially becomes ETL like spark.

One small issue is CDC + merge into columnstore means huge write amplification if you want fresh read on Analytics side, it is absurd especially for lakehouse tables (I have seen 100X for many OLTP workloads).

The only solution I found that we can trust agents creating, managing, running OLTP & OLAP queries is LTAP.

the fundamental mismatch i saw is "creating a new segment for each individual dml", it is possible to alleviate but i don't think there's a good general solution.
datalake~ datacake~ lakehouse~ cakehouse~ lol why would people care

Show HN: Pg_mooncake – Delta/Iceberg columnstore tables in Postgres

https://github.com/Mooncake-Labs/pg_mooncake

Hello HN, one of the founders of Mooncake Labs here.Today, we are launching pg_mooncake, an extension that brings columnstore tables with DuckDB execution to Postgres. Expect analytical performance akin to DuckDB on Parquet (clickbench results to come soon). You can run transactional updates, deletes, inserts on these tables, and they're written as Delta Lake tables (and soon Iceberg) to your...

( Read More... | 9 comments | 18 points | on HN )