Clickhouse really nailed this with the acquisition of peerdb. I used it with many terabyte databases and I essentially never thought about it. The only thing we really had to watch for was trying to replicate too much at once (because of the physical compute/io capacity of the postgres or clickhouse clusters).
This was basically Vertica's party trick for quite a long time to have a WOS and ROS formats for the same row and anti-caching between those two.
You could've built a similar system with dezebium and delta lake for quite some time but it would fail compactions, if you run it fast enough. I've seen Oracle GoldenGate 12c do this trick in 2014 or so, using Mysql as the cheap replica. But they are all fragile to schema updates in some direction.
The closest batteries-included equivalent to this is the Aurora -> Redshift bridge[1].
Aurora zero etl was a nightmare for us. Almost any schema changes require a VACUUM FULL for it to continue functioning. On a few occasions, it just stopped running without an obvious explanation, requiring slow and lengthy back and forth threads with AWS support. If it worked as advertised, it would be great, but I can't recommend it for any serious production system.
Clickhouse really nailed this with the acquisition of peerdb. I used it with many terabyte databases and I essentially never thought about it. The only thing we really had to watch for was trying to replicate too much at once (because of the physical compute/io capacity of the postgres or clickhouse clusters).
This was basically Vertica's party trick for quite a long time to have a WOS and ROS formats for the same row and anti-caching between those two.
You could've built a similar system with dezebium and delta lake for quite some time but it would fail compactions, if you run it fast enough. I've seen Oracle GoldenGate 12c do this trick in 2014 or so, using Mysql as the cheap replica. But they are all fragile to schema updates in some direction.
The closest batteries-included equivalent to this is the Aurora -> Redshift bridge[1].
[1] - https://aws.amazon.com/rds/aurora/zero-etl/
Aurora zero etl was a nightmare for us. Almost any schema changes require a VACUUM FULL for it to continue functioning. On a few occasions, it just stopped running without an obvious explanation, requiring slow and lengthy back and forth threads with AWS support. If it worked as advertised, it would be great, but I can't recommend it for any serious production system.
And this is, when it doesn't delete data randomly: https://github.com/trinodb/trino/issues/28885 (some enterprise open source was slop before AI even it seems)
Snowflake is a really amazing product. It's been a delight using it the last few years.
In FOSS land, Mooncake Labs had a pretty nice looking pg_mooncake for dumping into Iceberg. It would be fun to compare these! https://github.com/Mooncake-Labs/pg_mooncake