UUIDs are way over used. There is almost always a better key to use, usually a bigint for databases. If you're making some kind of leaderless distributed data store, then maybe, but even then there are other ID sharding strategies I'd go for first depending on the constraints.
For a single database, bigints are smaller and faster, with less footguns.
UUIDs can be nice for an opaque public ID, however I'd still prefer something like a Sqid for space and usability.
Yes this matters even more if you are doing a lot of joins. Naive string UUIDs are 32 bytes (though I use binary uuid in the post which is 16) compared to 8 bytes for a 64-bit int. This matters even more with sqlite as it uses varint encoding. The upshot of all this is your indexes take up a lot less space in memory.
They just mean you catch incorrect joins more easily because there is usually no overlap in keys between unrelated tables. Using int, you’re usually going to have some shared values between two unrelated tables.
Statistically impossible to inadvertently generate a collision using UUID keys. UUID is designed to be unique when generated across any computer system. Practically speaking if you have an exactly matching pair of UUIDs from disparate system you have found the exact record match. The name gives a hint "Universally unique identifier". -Not a cryptographer.
I am finding UUIDs help a lot if your primary schema consumer is an LLM.
Inappropriate aliasing of integer keys allows for silent errors in queries because it will actually return some result a lot of the time. A UUID is immune to this problem. The model recognizes its mistake a lot more reliably when previously non-empty tables start showing up empty after attempting a join.
Is this relevant for other databases? For postgres for example, which supports concurrent writers, wouldn't sequential keys lead to contention on the page at the frontier?
Small nit: uuid7 is 128 bits (16 bytes) by definition. So there’s no need to convert it to binary. It already is. Unless you’re working with a stringified version of the uuid7.
> and you should always convert that to binary to optimize everything
I disagree. I tried this once. Now you need a client access layer to touch the DB in any context. All your console tools no longer work well or at all. If they show up in URLs you need to deoptimize them for transport.
You give up a lot of convenience for this optimization. You should be absolutely sure your design requires it before using it.
Yes it's writing to disk (on a M1 mac which has terribly slow fsync). But, because of the transaction the fsync dance is done once per batch. Each row is the id + a 50 byte data blob.
There's only one index so there's no real write amplification. The numbers will go down as you add more data and indexes.
For a single database, bigints are smaller and faster, with less footguns.
UUIDs can be nice for an opaque public ID, however I'd still prefer something like a Sqid for space and usability.
But be careful!! Javascript WILL interpret your bigints as Number() and round them down because they are too big without telling you!!!
Famously seen by every snowflake user that has interacted with Javascript, quite an annoying problem.
In JS - BigInt is 64bit integer.
In anything else - BigInt is a arbitrarily large integer.
Node.js drivers will correctly read int64 as string or bigint, not number.
E.g. pg for PostgreSQL
Maybe there’s a buggy driver but I don’t know it.
It does not actually make it impossible to query the wrong table it just tells you quickly when you’ve done so.
Inappropriate aliasing of integer keys allows for silent errors in queries because it will actually return some result a lot of the time. A UUID is immune to this problem. The model recognizes its mistake a lot more reliably when previously non-empty tables start showing up empty after attempting a join.
How much trouble does SQLite reysing rowid's actually cause?
Regular rowids are definitely the way to go if you can use them.
I disagree. I tried this once. Now you need a client access layer to touch the DB in any context. All your console tools no longer work well or at all. If they show up in URLs you need to deoptimize them for transport.
You give up a lot of convenience for this optimization. You should be absolutely sure your design requires it before using it.
https://sqlite.org/inmemorydb.html
There's only one index so there's no real write amplification. The numbers will go down as you add more data and indexes.