"Serverless" DBs are also very pricey if you consider everything. Instead, it isn't actually that hard to do some work loads at huge scale for cheap, two good articles on this (one discord, one ours)
- https://blog.discordapp.com/how-discord-stores-billions-of-m...
- https://www.youtube.com/watch?v=x_WqBuEA7s8 (100M records/day for $10 total cost, server, disk, S3 backup!)
Gun is new to me. You have a good way of handling distributed consistency. It's intriguing that the system still can reach consistency even if every node loses network connectivity temporarily. Is there any academic work behind this?
For non-academics though, I did a comic strip explainer for the layperson (as distributed systems are often hyped up with elitist jargon) here: http://gun.js.org/distributed/matters.html !
The prototype shown in the video was specific to append-only data and was done last year, we recently rewrote the system to be more generalizable using a radix trie structure and have released an alpha of it with the Radix Storage Engine (RSE) in the main repo: https://github.com/amark/gun
Let me know if you need help with any/all of that, or more links/resources (docs are somewhat scarce on it currently, sadly), and I'll do what I can!
Although, I can't resist but to leave this one last animated explainer gif that shows what a radix looks like: http://gun.js.org/see/radix.gif
You can also throw a light DB (mySql, SqlExpress, Postgres) on a VM that you already have running 24/7, that would make the additional cost zero.
Of course you are still going to need to curate your dev/qa data (through replication or periodic backup/restore) because shit data is hard to code against, not to mention debug against.
He also seems to imply that you have to keep your test db's running all day instead of simply paying for them by the hour. :|
If this is the premise for serverless database it's a weak start. If you really need lightweight DBMS for testing just run MySQL or PostgreSQL in Docker. If you really need access to production-like data (e.g., a lot of it so you get realistic distributions) run the same DBMS on cheap hardware or cheap instances. In both cases you can use persistent volumes and shut down when things are not in use. Few people really care if it takes a few minutes to spin up the test environment.
As for the main point of Aurora offering a "Serverless" architecture it looks as if what they've really done is enabled the DBMS compute layer to scale up and down quickly. I wonder if this optimization fell out of pushing redo log management down into the storage layer. (See Section 3.1 https://www.allthingsdistributed.com/files/p1041-verbitski.p... for details.)