[fauigerzigerk]

The problem I have with CRDTs is that while being conflict-free in a technical sense they don't allow me to express application level constraints.

E.g, how do you make sure that a hotel room cannot be booked by more than one person at a time or at least flag this situation as a constraint violation that needs manual intervention?

It's really hard to get anywhere close to the universal usefulness and simplicity of centralised transactions.

[NickM]

Yeah, this is a limitation, but generally if you have hard constraints like that to maintain, then yeah you probably should be using some sort of centralized transactional system to avoid e.g. booking the same hotel room to multiple people in the first place. Even with perfect conflict resolution, you don't want to tell someone their booking is confirmed and then later have to say "oh, sorry, never mind, somebody else booked that room and we just didn't check to verify that at the time."

But this isn't a problem specific to CRDTs, it's a limitation with any database that favors availability over consistency. And there are use cases that don't require these kinds of constraints where these limitations are more manageable.

[fauigerzigerk]

I agree, hotel booking is not a great example.

I think CRDTs would be applicable to a wider range of applications if it was possible to specify soft constraints.

So after merging your changes you can query the CRDT for a list of constraint violations that need to be resolved.

[fatherzine]

"How do you make sure that a hotel room cannot be booked by more than one person at a time" Excellent question! You don't. Instead, assuming a globally consistent transaction ordering, eg Spanner's TrueTime, but any uuid scheme suffices, it becomes a tradeoff between reconciliation latency and perceived unreliability. A room may be booked by several persons at a time, but eventually only one of them will win the reconciliation process.

    A: T.uuid3712[X] = reserve X
    ...
    B: T.uuid6214[X] = reserve X  // eventually loses to A because of uuid ordering
    ...
    A<-T.uuid6214[X]: discard T.uuid6214[X]
    ...
    B<-T.uuid3712[X]: discard T.uuid6214[X], B.notify(cancel T.uuid6214[X])
    -----
    A wins, B discards

The engineering challenge becomes to reduce the reconciliation latency window to something tolerable to users. If the reconciliation latency is small enough, then a blocking API can completely hide the unreliability from users.