A Comprehensive Study of Convergent and Commutative Replicated Data Types
📜 Abstract
Eventual consistency is widely believed to be necessary in large-scale distributed systems, in order to ensure high availability, improved responsiveness, and partition tolerance. However, while eventual consistency allows replicas to temporarily diverge, consistency must be restored when updates cease. To this end, we propose and study sufficient conditions that ensure eventual consistency. One important technique is to use a replicated data type (RDT) that ensures strong eventual consistency (SEC). An object satisfies SEC if it guarantees eventual consistency while converging towards the same state in every replica, regardless of update order. This requires that concurrent updates commute. Two classes of SEC replicated data types are identified: State-based convergent replicated data types (CvRDTs) and Operation-based commutative replicated data types (CmRDTs). This work defines these two classes precisely, and explains their properties, advantages, and limitations, with a comprehensive set of algorithms and their proof of correctness. We analyze the trade-offs between time/space complexity and consistency, delivering a set of useful design principles for highly available distributed systems.
✨ Summary
This paper provides a foundational analysis of Convergent and Commutative Replicated Data Types (CRDTs) and is highly influential in the field of distributed computing. The authors introduce a framework for understanding how different types of replicated data can achieve strong eventual consistency, a concept crucial for developing high-performance distributed systems. The impact of this paper is notably seen in various follow-up studies and practical applications. For instance, it is cited in The Art of Multiprocessor Programming and CRDT Development. Additionally, academic works often refer to this paper when discussing consistency models and CRDT optimizations, demonstrating its importance in advancing both theoretical and applied aspects of the field. Consequently, this paper has contributed significantly to advancements in distributed databases and conflict-free replicated data types used by industry leaders like Riak and Microsoft Azure.