Almost every time I see CRDTs mentioned it’s used as a magic device that makes conflicts disappear. The details, of course, are not mentioned.

Technically an algorithm that lets the last writer win is a CRDT because there is no conflict.

Making a true system that automatically merges data while respecting user intent and expectations can be an extremely hard problem for anything complex like text.

Another problem is that in some situations using a CRDT to make the conflict disappear isn’t even the right approach. If two users schedule a meeting for the same open meeting room, you can’t avoid issues with an algorithm. You need to let them know about the conflict so they can resolve the issue.

> Technically an algorithm that lets the last writer win is a CRDT because there is no conflict.

Yes. It’s called a LWW register in the literature. Usually a MV (multi value) register is more useful. When there is a conflict, MV registers store all conflicting values and make any subsequent reader figure out what to do.

But for my money, usually what you want is something operation based. Like, if we both append to a transaction list, the list should end up with both items. Operation based CRDTs can handle any semantics you choose - so you can mix and match different merging approaches based on the application. And the storage for LWW and MV is the same, so you can start simple and grow your app as needed.

IMO the reason local first software is still not popular is the same reason encrypted messaging apps took awhile. There’s a lag from good CS research enabling a class of applications and good implementations being available with good UX. Most CRDT implementations are still pretty new. Automerge has been really slow until quite recently. Most libraries don’t support ephemeral data or binary blobs well. And there aren’t a lot of well defined patterns around user login and authentication. Local first apps today have a lot of work ahead of them to just exist at all. Give it some time.

The details appear to be not giving a damn about changes to data. I personally wouldn't describe that as "converging". As it says, this is "Last Write Wins", which is great if the last writer is always correct.

"If it’s older → ignore" -- yea, I guess that's a solution but I would really have to look for the problem.

I've gone down this road and considered github (or similar) as the backing database. In the end, I just don't have an answer that isn't specific to nearly every field that might be entered. A notes field might be appended. First in might be important, or last in (if it can be trusted as correct). Usually it's something like, "which of these two did you meant to capture?"

I’ve never really thought about this - how does Outlook handle this? Has anyone received a “sorry, that room you reserved actually wasn’t available; talk to this other dude who reserved it too” message after reserving a meeting room?

Or does it just double book the room? Or is there a global lock on any transaction affecting a meeting room, so only one goes through? (Feels like it doesn’t scale)

You can resolve it with an algorithm, like so

- prefer seniority - prefer pay scale - prefer alphabetical - roll dice

That’s how a business would probably do it since the first two alone align with how the business already values their Human Resources, which would translate to “the objects that the Human Resources compete for”

> Technically an algorithm that lets the last writer win is a CRDT because there is no conflict.

Your comment shows some ignorance and a complete misunderstanding of the problem domain.

The whole point of CRDTs is that the set o operations supported is designed to ensure that conflict handling is consistent and deterministic across nodes,and the state of all nodes involved automatically converge to the same state.

Last-write-wins strategies offer no such guarantees. Your state diverges uncontrollably and your system will become inconsistent at the first write.

> Making a true system that automatically merges data while respecting user intent and expectations can be an extremely hard problem for anything complex like text.

Again, this shows a complete misunderstanding of the problem domain. CRDTs ensure state converges across nodes, but they absolutely do not reflect "user intent". They just handle merges consistently. User intent is reflected by users applying their changes, which the system then propagates consistently across nodes.

The whole point of CRDTs is state convergence and consistency.