A CAPable distributed programming model

Myter, Florian; Scholliers, Christophe; Meuter, Wolfgang De

doi:10.1145/3276954.3276957

Cited by 9 publications

(4 citation statements)

References 25 publications

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“…Similar to our work, CAPtain [14] supports both consistency and availability by means of consistent and available objects. CAPtain's meta-object protocol (MOP) allows experts to change the model's internals, for instance to customise replication.…”

Section: Related Worksupporting

confidence: 57%

Squirrel: an extensible distributed key-value store

Porre

Boix

2019

Proceedings of the 4th ACM SIGPLAN International Workshop on Meta-Programming Techniques and Reflection

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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.

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Section: Related Worksupporting

confidence: 57%

Squirrel: an extensible distributed key-value store

Porre

Boix

2019

Proceedings of the 4th ACM SIGPLAN International Workshop on Meta-Programming Techniques and Reflection

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“…NoSQL stores are non-transactional, thereby creating difficulties in the advent of failures and/or concurrent updates. The lack of atomicity causes the problem in multiple rows of updates [61]. As mentioned earlier, time or place specific applications require the use of temporal and spatial databases, which is still the Achilles' heel for both SQL and NoSQL.…”

Section: No One Cure-them-all Database Resulting In Polyglot Persistencementioning

confidence: 99%

A Review of Polyglot Persistence in the Big Data World

Khine

Wang

2019

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The inevitability of the relationship between big data and distributed systems is indicated by the fact that data characteristics cannot be easily handled by a standalone centric approach. Among the different concepts of distributed systems, the CAP theorem (Consistency, Availability, and Partition Tolerant) points out the prominent use of the eventual consistency property in distributed systems. This has prompted the need for other, different types of databases beyond SQL (Structured Query Language) that have properties of scalability and availability. NoSQL (Not-Only SQL) databases, mostly with the BASE (Basically Available, Soft State, and Eventual consistency), are gaining ground in the big data era, while SQL databases are left trying to keep up with this paradigm shift. However, none of these databases are perfect, as there is no model that fits all requirements of data-intensive systems. Polyglot persistence, i.e., using different databases as appropriate for the different components within a single system, is becoming prevalent in data-intensive big data systems, as they are distributed and parallel by nature. This paper reflects the characteristics of these databases from a conceptual point of view and describes a potential solution for a distributed system-the adoption of polyglot persistence in data-intensive systems in the big data era.

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“…In contrast, ECROs may avoid coordination by reordering unsafe operations in order not to break invariants, based on the novel combination of static analyses with our execution model. Several programming languages and programming models [De Porre et al 2020;Holt et al 2016;Köhler et al 2020;Milano and Myers 2018;Myter et al 2018;Zaza and Nystrom 2016] support mixing consistency levels safely to some extent. However, there is currently no technique that can automatically derive commutative operations (or correct merge procedures) from sequential data types without programmer intervention.…”

Section: Related Workmentioning

confidence: 99%

ECROs: building global scale systems from sequential code

Porre

Ferreira

Preguiça

et al. 2021

Proc. ACM Program. Lang.

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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.

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A CAPable distributed programming model

Cited by 9 publications

References 25 publications

Squirrel: an extensible distributed key-value store

Squirrel: an extensible distributed key-value store

A Review of Polyglot Persistence in the Big Data World

ECROs: building global scale systems from sequential code

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