automerge-rs VS crdt-benchmarks

See also, Autosurgeon (with a 0.3.0 release today), which is a higher level API on top of Automerge for Rust:

I'm building a mobile app with a server backend, and I was looking for resources to build them in an offline-first way (since unlike on the browser, people expect to use apps offline, if they can, such as fitness or habit trackers).

I found the concept of conflict-free relational data types (CRDTS) interesting as it allows you to have fully offline experiences while also having a conflict-free syncing experience. I was looking for some good libraries and came across automerge [0] and yrs [1], but both had some rough APIs as they're primarily low-level Rust libraries that are wrapped by higher-level TypeScript APIs.

Autosurgeon wraps the low-level API of automerge to make it much more ergonomic, closer to the TypeScript experience, but in Rust of course. You can for example use `struct`s which autosurgeon will serialize and deserialize automatically, which is not present in base automerge, which focuses more on string keys and arbitrary values.

I am planning on using this together with Flutter and flutter_rust_bridge [2] in order to use this same Rust library everywhere. In this case, the server just becomes another (albeit more privileged) client.

[0] https://github.com/automerge/automerge-rs

[1] https://github.com/y-crdt/y-crdt

[2] https://github.com/fzyzcjy/flutter_rust_bridge

I found the concept of conflict-free relational data types (CRDTS) interesting as it allows you to have fully offline experiences while also having a conflict-free syncing experience. I was looking for some good libraries and came across automerge and yrs, but both had some rough APIs as they're primarily low-level libraries that are wrapped by TypeScript APIs.

Yes, the plan is to use PostgreSQL. I had a discussion with one of the devs in this ticket about the strategy for this.

In any case, my current plan is to use Automerge for the data handling itself (so I can easily do collaboration), but that crate doesn't handle on-disk storage. For this I need another solution, and a K/V store is well suited for this task.

15 years working in software, Rust has been my favourite language for the last 2. Recently completed a contract to prototype a distributed Tailscale-inspired VPN built on Ink and Switch's CRDT project automerge-rs.

Complex topic. There's a very easy-to-use CRDT library for Rust (automerge), while there isn't much support for operational transforms (although Aper is new to me, I have to check it out).

I've been watching automerge-rs like a hawk, because they seem to be the only CRDT implementation where you don't need a Mathematics master to understand how to use it. They've been working on a rewrite for the last two years, hopefully they'll do a new release soon.

https://github.com/automerge/automerge-rs

By the way despite that particular repo (@localfirst/state) last being touched 6 months ago, Herb Caudill definitely seems still active in this space (I believe he's been working on other parts of this more recently -- e.g. ideas about authentication), and I think automerge development itself is quite active right now leading up to a 1.0 release which seems fairly imminent, for which a lot of fundamental work has been done, also coordinating with automerge-rs.

Author of Yjs here. I'm all for faster data structures. But only benchmarking one dimension looks quite fishy to me. A CRDT needs to be adequate at multiple dimensions. At least you should describe the tradeoffs in your article.

The time to insert characters is the least interesting property of a CRDT. It doesn't matter to the user whether a character is inserted within .1ms or .000000001ms. No human can type that fast.

It would be much more interesting to benchmark the time it takes to load a document containing X operations. Yjs & Yrs are pretty performant and conservative on memory here because they don't have to build an index (it's a tradeoff that we took consciously).

When benchmarking it is important to measure the right things and interpret the results somehow so that you can give recommendations when to use your algorithm / implementation. Some things can't be fast/low enough (e.g. time to load a document, time to apply updates, memory consumption, ..) other things only need to be adequate (e.g. time to insert a character into a document).

Unfortunately, a lot of academic papers set a bad trend of only measuring one dimension. Yeah, it's really easy to succeed in one dimension (e.g. memory or insertion-time) and it is very nice click-bait. But that doesn't make your CRDT a viable option in practice.

I maintain a set of benchmarks that tests multiple dimensions [1]. I'd love to receive a PR from you.

[1]: https://github.com/dmonad/crdt-benchmarks

Diamond types author here! Congratulations on getting your crdt working! It’s lovely to see a new generation of CRDTs which have decent performance.

And nice stuff implementing peritext! I’d love to do the same in diamond types at some point. You beat me to it!

Im building a little repository of real world collaborative editing traces to use when benchmarking, comparing and optimising text based CRDTs[1]. The automerge-perf editing trace isn’t enough on its own. And we’re increasingly converging on a format for multi user concurrent editing traces too[2]. It’d be great to add some rich text editing traces in the mix if you’re interested in recording something, so we can also compare how peritext performs in different systems.

Anyway, welcome to the community! Love to have more implementations around!

https://github.com/josephg/crdt-benchmarks

https://github.com/dmonad/crdt-benchmarks/issues/20

So yes, a particularly large document is not the norm but it can happen.

JavaScript CRDTs can be quite performant, see the Yjs benchmarks: https://github.com/dmonad/crdt-benchmarks