crdt-benchmarks VS automerge

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

Cool! It'd be interesting to see those CRDT implementations added to Kevin Jahns' CRDT Benchmarks page[1]. The LogootSplit paper looks interesting. It looks like xray is abandoned, and I'm not sure about teletype. Though teletype's CRDT looks to be entirely implemented in javascript[2]? If the authors are around I'd love to see some benchmarks so we can compare approaches and learn what actually works well.

And I'm not surprised these techniques have been invented before. Realising a tree is an appropriate data structure here is a pretty obvious step if you have a mind for data structures.

To name it, I often find myself feeling defensive when people read my work and respond with a bunch of links to academic papers. Its probably totally unfair and a complete projection from my side, but I hear a voice in my head reword your comment to instead say something awful like: "Cool, but everything you did was done before. Even if they didn't make any of their work practical, usable or good they still published first and you obviously didn't do a good enough literature review if you didn't know that." And I feel an unfair defensiveness arise in me as a result that wants to find excuses to dismiss the work, even if the work might be otherwise interesting.

Its hard to compare their benchmark results because they used synthetic randomized editing traces, which always have different performance profiles than real edits for this stuff. Their own university gathered some great real world data in an earlier study. It would have been much more instructive if that data set was used here. At a glance their RAM usage looks to be about 2 orders of magnitude worse than diamond-types or yjs. And their CPU usage... ?? I can't tell because they have no tables of results. Just some hard to read charts with log scales, so you can't even really eyeball the figures. So its really hard to tell if their work ends up performance-competitive without spending a couple days getting their enterprise style java code running with a better data set. Do you think thats worth doing?

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

[2] https://github.com/atom/teletype-crdt

Thank you! I actually kind of cheated and didn't have to implement any of that myself because Firebase took care of it. But when I was considering how to build Calenday, those were on my mind. I had read about CRDTs on Figma's blog (https://www.figma.com/blog/how-figmas-multiplayer-technology...) and was considering using something like this to ease the burden on implementation: https://github.com/automerge/automerge