We've dedicated this year to performance with a storage engine rewrite. We'll have some performance wins coming in the back half of the year. We think we can get under 2X MySQL.
It also requires more disk. Each change is at least on average 4K on disk. So, you might need more/bigger hard drives.
In your benchmark it's only 2.1–7.4 times slower than MySQL, average 4.4. And any database someone could fit on a disk 20 years ago (I forget, maybe 8 GB?) fits in RAM now, which makes it about 256 times faster, which is a lot bigger than 4.4. You can get a 20 TB disk now, which is enough space So anything that could be done with MySQL 20 years ago can be done faster and cheaper with Dolt now, which covers, I think the technical term is, a fucking shitload of applications. It probably includes literally every 20th-century application of relational databases.
Well, except for things that have over 5 billion transactions (20 TB ÷ 4 kB/txn) over their lifetime, I guess, so it might be important to find a way to compact that 4K. 5 billion transactions is 19 months at 100 TPS. If you could get that down to 256 bytes it would be almost 25 years of 100 TPS.
Also, as I understand it, and correct me if I'm wrong here, that 4.4× slowdown buys you a bulletproof and highly performant and scalable strategy for backups (with PITR), staging servers, data warehousing, readslaves, disk error detection and recovery, cryptographically secure audit logs, bug reproduction, and backtesting. Along with the legal security the Apache 2 license gives you, which you don't have with Datomic.
Sounds fantastic! It sounds like you're selling its performance a bit short. If someone is really concerned about such a small performance loss they probably aren't really in the market for a new RDBMS.
It's slower. This is `sysbench` Dolt vs MySQL.
https://docs.dolthub.com/sql-reference/benchmarks/latency
We've dedicated this year to performance with a storage engine rewrite. We'll have some performance wins coming in the back half of the year. We think we can get under 2X MySQL.
It also requires more disk. Each change is at least on average 4K on disk. So, you might need more/bigger hard drives.