Conflict-free replicated data types (CRDTs) aid programmers develop highly available and scalable distributed systems. However, the literature describes only a limited portfolio of conflict-free data types and implementing custom ones requires additional knowledge of replication and consistency techniques. As a result, programmers resort to ad hoc solutions which are error-prone and result in brittle systems. In this paper, we introduce strong eventually consistent replicated objects (SECROs), a general-purpose data type for building available data structures that guarantee strong eventual consistency (SEC) without restrictions on the operations. To evaluate our solution we compare a realtime collaborative text editor built atop SECROs with a state-of-theart implementation that uses JSON CRDTs. This comparison quantifies various performance aspects. The results show that SECROs are truly general-purpose and memory efficient.

To ease the development of geo-distributed applications, replicated data types (RDTs) offer a familiar programming interface while ensuring state convergence, low latency, and high availability. However, RDTs are still designed exclusively by experts using ad-hoc solutions that are error-prone and result in brittle systems. Recent works statically detect conflicting operations on existing data types and coordinate those at runtime to guarantee convergence and preserve application invariants. However, these approaches are too conservative, imposing coordination on a large number of operations. In this work, we propose a principled approach to design and implement efficient RDTs taking into account application invariants. Developers extend sequential data types with a distributed specification, which together form an RDT. We statically analyze the specification to detect conflicts and unravel their cause. This information is then used at runtime to serialize concurrent operations safely and efficiently. Our approach derives a correct RDT from any sequential data type without changes to the data type's implementation and with minimal coordination. We implement our approach in Scala and develop an extensive portfolio of RDTs. The evaluation shows that our approach provides performance similar to conflict-free replicated data types for commutative operations, and considerably improves the performance of non-commutative operations, compared to existing solutions.

Conflict-free replicated data types (CRDTs) [7] aid programmers develop highly available and scalable distributed systems. However, CRDTs require operations to commute which is not practical. This means that programmers cannot replicate regular objects without worrying about concurrency. In this paper, we introduce strong eventually consistent replicated objects (SECROs), a generic data type that is highly available and guarantees strong eventual consistency (SEC) without imposing restrictions on its operations. CCS CONCEPTS• Software and its engineering → Distributed systems organizing principles; Consistency;

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Distributed key-value (KV) stores are a rising alternative to traditional relational databases since they provide a flexible yet simple data model. Recent KV stores use eventual consistency to ensure fast reads and writes as well as high availability. Support for eventual consistency is however still very limited as typically only a handful of replicated data types are provided. Moreover, modern applications maintain various types of data, some of which require strong consistency whereas other require high availability. Implementing such applications remains cumbersome due to the lack of support for data consistency in today's KV stores. In this paper we propose Squirrel, an open implementation of an in-memory distributed KV store. The core idea is to reify distribution through consistency models and protocols. We implement two families of consistency models (strong consistency and strong eventual consistency) and several consistency protocols, including two-phase commit and CRDTs.CCS Concepts • Information systems → Key-value stores; Data replication tools; Distributed database transactions.