The top concern I've gotten from dev teams when proposing HA distributed postgres (e.g through RDS Aurora global) is that eventual consistency is not suitable for many workloads.
Does Neki solve for this, and if so how? My understanding of CAP theorem is that this basically requires some compromises around availability, but I'm curious as to what that looks like in practice here.
Assuming it works the same way as their MySQL product, Vitess:
The usual way to run it is that you partition your db based on something like a user, so that single user gets a consistent DB, but anything cross-shard may not be.
I know when I worked at Block, Cashapp was using Vitess and getting cross-shard DB writes down and functioning correctly was one of the major blockers to adoption. (though I just did tls management for vitess and didn't write any workloads on top of it, so my impression might be a bit off)
Same here, first thing I need to know when considering a distributed system is how consistency is handled. If it's eventual consistency, what is the replication lag like? If it's strong consistency, can their network handle that? What happens when a node goes down?
I love to see this but as a heavy Vitess/MySQL user I do fear the split focus from PlanetScale. Hoping to see continued improvements on the Vitess side as well.
Selfish doubts aside, congrats to Planetscale on the launch!
don't worry, we still give a lot of love to vitess. at the end of the day they are both databases. the beauty of doing both is we can take learnings from each product and apply it to the other.
We went as far as we could on GCP before PlanetScale. Spanner is amazing but also amazingly expensive. And CloudSQL, also amazing as long as you don’t need write scaling. PlanetScale (Vitess+MySQL plus their branching / deployment and monitoring tools) is just not a combination offered on GCP. And while I didn’t use Aurora, from talking to and exploring AWS it doesn’t really have this combination either.
The largest database to ever run on Aurora MySQL runs on PlanetScale, and the largest database to ever run on Aurora limitless also runs on PlanetScale.
I see no mention of foreign keys, or any other constraints, across shards. If, as I suspect, they're not implemented, it would still be useful but at the level of Spanner 10 years ago.
Are you one of the developers ? If so, you need to add a specific page explaining in detail the guarantees that this gives.
For example: point 08 says "Assign different tables or workloads to different shard groups" and point 02 says "Split hot shards as workloads grow". How do those interact ? Can a single table be split across multiple shards ? If so don't you need 2pc to enforce primary key constraints ?
Does Neki solve for this, and if so how? My understanding of CAP theorem is that this basically requires some compromises around availability, but I'm curious as to what that looks like in practice here.
The usual way to run it is that you partition your db based on something like a user, so that single user gets a consistent DB, but anything cross-shard may not be.
I know when I worked at Block, Cashapp was using Vitess and getting cross-shard DB writes down and functioning correctly was one of the major blockers to adoption. (though I just did tls management for vitess and didn't write any workloads on top of it, so my impression might be a bit off)
Selfish doubts aside, congrats to Planetscale on the launch!
The pitch is compelling. I wonder how many teams will be able to operate sharded database setups in production as a result of this.
For example: point 08 says "Assign different tables or workloads to different shard groups" and point 02 says "Split hot shards as workloads grow". How do those interact ? Can a single table be split across multiple shards ? If so don't you need 2pc to enforce primary key constraints ?
The intro pages just read as AI slop.
I am looking for interdimensional and interuniversal scale. Which of you trust fund babies has a startup which is working on this problem?