In my experience, this depends a lot more on the implementation than the CRDT algorithm. If you implement Causal Trees directly (as a tree with one node per cha

In my experience, this depends a lot more on the implementation than the CRDT algorithm. If you implement Causal Trees directly (as a tree with one node per char), it will be tolerably fast but use a lot of memory + storage. If you instead group chars into "runs" of sequentially-inserted chars and only store one Causal Tree node per run, it should be quite efficient. Yjs (a widely used text CRDT) describes these sort of opts here: https://blog.kevinjahns.de/are-crdts-suitable-for-shared-editing/ https://blog.kevinjahns.de/are-crdts-suitable-for-shared-edi... For a different tree-based CRDT, I did a head-to-head comparison of implementations that use a node-per-char (Fugue Simple) vs runs (Fugue), with results in Section 5 of this paper: https://arxiv.org/abs/2305.00583 https://arxiv.org/abs/2305.00583