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Exactly! Why unifying storage, which opens up a can of trade-offs.
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.

If you product is CDC based (peerdb) you don’t want storage to support this :)

This architecture is better for OLTP because all maintenance operations are moved to storage AND it has all other benefits such as LTAP that emerge from having a scalable storage.

;) sounding good on paper vs how it works in practice (supporting demanding real-time OLTP/OLAP workloads) are completely different ball games.

Separately, I understand taking care of it at storage level, but still don’t get “unifying storage” or “zero copy”.

Anyways, I’ll stop now. Good to see all the innovation happening on converging OLTP/OLAP front. Each with a different approach and perspective. :)

this is all so funny, gl to everyone
Did you even read the blog? Or are you just throwing shade because you are working on a competitive product based on CDC?
Oh no, I did read the blog. Not throwing shade at anyone here—the blog is great. It just doesn’t provide real-world evidence, and it opens up a bunch of technical questions that I’m trying to understand. that’s exactly what HN is for. :)