Matrix-CRDT VS datahike

Another interesting and peculiar approach would be to use Matrix, which is chat and collaboration framework that is completely decentralised. Essentially, in this way Scrivano would translate pen input into chat messages that are sent to other users who receive them in real time. One advantage of this approach is that the collaborative notes will remain accessible even after you go offline and multiple users will be able to collaborate on a single note just like they would in a group chat. There are already apps that make use of this idea (e.g. see Matrix-CRDT or TheBoard), but when I tried this it last time didn't work very well and I'm not sure whether this is a limitation of the service or of the specific implementation I tried.

1. This is complicated. There is a notion of power_level, which you can set to different events. So you can set "send message" to power level 30, and any user with a "power level" of 30 or more will be able to send messages. Those power levels (and the required level to send an event) are granted by the room creator.

There is, however, no power_level associated with reading messages. I think you need to be joined to a room to send messages, and to be joined, you need to be able to read messages by design. So the "inbox" model doesn't seem representable to me. But maybe I'm missing something!

2. Yes. Events can refer to prior events to modify them, e.g. you can "edit" a previous message by appending a new message of type "msg.edit" (made up type, not sure what the exact it), specifying the old message id, and the new text. For matrix-based CRDT, see Matrix-CRDT[1], a Yjs backend using Matrix.

[1]: https://github.com/YousefED/Matrix-CRDT

Have you checked out Matrix? It's specifically a protocol (they've used OpenWhisper) but people are using it like a social media platform (specifically like IRC). There's even people doing google docs like services. I'm going to link a HN thread from that last link because others are just talking about Matrix and that'll likely be helpful to you.

Show HN: Matrix-CRDT – real-time collaborative apps using Matrix as backend\ (2 comments)

Datahike [0] provides similar functionality to datomic and is open source. It lacks some features however that Datomic does have [1].

[0]: https://github.com/replikativ/datahike

You can also consider other durable Datalog options like datahike or datalevin which can work either as lib (SQLite style) or in a client-server setup; if you want to play with bi-temporality XTDB is a rock solid option with very good support and documentation.

Check https://github.com/replikativ/datahike

Oh really interesting. I didn't know about that. I was actually going threw the old Mendat code base and was considering using that.

I would really like a pure Rust version of Datomic for embed use cases.

There is all also Datahike, that is going in that direction too. It is maintained and actively developed.

https://github.com/replikativ/datahike

Having an Datomic like store backed by something like this.

https://github.com/replikativ/datahike

Is an Open Source variant of Datomic.

Lambdaforge wants to eventually have this work with CRDTs.

Using the Matrix ecosystem for this is quite interesting as it solves many problems for you already.

Unlike some other commenters, I agree that graph models are usually a better fit for most data than relational models. There's been some interesting work in recent years developing this idea: in the Clojure world there's Datomic, XTDB, and a host of competitors, all of which build on work from Semantic Web/SPARQL/triplestores and logic programming. Some are even intended to be used as primary datastores: they support some amount of schema and constraints, have well-defined consistency and ACID guarantees, etc. This makes them unlike graph databases like Neo4J and others, which fill an architectural role more like Elasticsearch as a read-optimization tool. Here's an interesting talk making a case for triple-based databases.

Have a look at https://github.com/replikativ/datahike and https://github.com/replikativ/datahike-postgres

There is now a datahike linux native image preview available: https://github.com/replikativ/datahike/releases/tag/preview

And implemented as a full-on datastore queried via Datalog: https://github.com/replikativ/datahike