Collabs: A Flexible and Performant CRDT Collaboration Framework
Abstract
A collaboration framework is a distributed system that serves as the data layer for a collaborative app. Conflict-free Replicated Data Types (CRDTs) are a promising theoretical technique for implementing collaboration frameworks. However, existing frameworks are inflexible: they are often one-off implementations of research papers or only permit a restricted set of CRDT semantics, and they do not allow app-specific optimizations. Until now, there was no general framework that lets programmers mix, match, and modify CRDTs. We solve this with Collabs, a CRDT-based collaboration framework that lets programmers implement their own CRDTs, either from-scratch or by composing existing building blocks. Collabs prioritizes both semantic flexibility and performance flexibility: it allows arbitrary app-specific CRDT behaviors and optimizations, while still providing strong eventual consistency. We demonstrate Collabs's capabilities and programming model with example apps and CRDT implementations. We then show that a collaborative rich-text editor using Collabs's built-in CRDTs can scale to over 100 simultaneous users, unlike existing CRDT frameworks and Google Docs. Collabs also has lower end-to-end latency and server CPU usage than a popular Operational Transformation framework, with acceptable CRDT metadata overhead.
Cite
@article{arxiv.2212.02618,
title = {Collabs: A Flexible and Performant CRDT Collaboration Framework},
author = {Matthew Weidner and Huairui Qi and Maxime Kjaer and Ria Pradeep and Benito Geordie and Yicheng Zhang and Gregory Schare and Xuan Tang and Sicheng Xing and Heather Miller},
journal= {arXiv preprint arXiv:2212.02618},
year = {2023}
}
Comments
18 pages, 19 figures