Scalable atomic visibility with RAMP transactions

Bailis, Peter; Fekete, Alan; Hellerstein, Joseph M.; Ghodsi, Ali; Stoica, Ion

doi:10.1145/2588555.2588562

Cited by 81 publications

(126 citation statements)

References 35 publications

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“…This illustrates in two real-word scenarios how the CAP theorem of Brewer [59] impacts transactional datastores. In a near future, we plan to refine this study by supporting additional criteria and protocols (e.g., read atomicity [2] or opacity [60]). Another direction of interest is the dynamic adaptation of consistency to the workload.…”

Section: Resultsmentioning

confidence: 99%

“…In case their size equals O(m), with m = |Objects|, they allow a permissive computation of all the partial consistent snapshots [15,Theorem 1]. 2 In the current state of the implementation, G-DUR supports the TS, VC, VTS, GMV and PDV versioning mechanisms.…”

Section: Version Trackingmentioning

confidence: 99%

“…On the one hand, they should be highly parallel and distributed in order to be fast, responsive and available; on the other, application servers must remain synchronized, in order to maintain consistency. Because of this tension, there exists a large number of distributed transaction models and protocols with different trade-offs: from very strongly synchronized ones [1], to ones with lots of parallelism [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

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G-Dur

Ardekani¹,

Sutra

Shapiro³

2014

Proceedings of the 15th International Middleware Conference on - Middleware '14

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A large family of distributed transactional protocols have a common structure, called Deferred Update Replication (DUR). DUR provides dependability by replicating data, and performance by not re-executing transactions but only applying their updates. Protocols of the DUR family differ only in behaviors of few generic functions. Based on this insight, we offer a generic DUR middleware, called G-DUR, along with a library of finely-optimized plug-in implementations of the required behaviors. This paper presents the middleware, the plugins, and an extensive experimental evaluation in a geo-replicated environment. Our empirical study shows that: (i) G-DUR allows developers to implement various transactional protocols under 600 lines of code; (ii) It provides a fair, apples-to-apples comparison between transactional protocols; (iii) By replacing plugs-ins, developers can use G-DUR to understand bottlenecks in their protocols; (iv) This in turn enables the improvement of existing protocols; and (v) Given a protocol, G-DUR helps evaluate the cost of ensuring various degrees of dependability.

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Section: Resultsmentioning

confidence: 99%

Section: Version Trackingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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G-Dur

Ardekani¹,

Sutra

Shapiro³

2014

Proceedings of the 15th International Middleware Conference on - Middleware '14

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“…Since neither serializability nor strong consistency are achievable when network partitions may occur [13] RDBMSs usually choose ACID over high availability [14], [15]. Brewer's CAP theorem states that of the three properties availability (A), consistency (C) and partition tolerance (P), any distributed database system can achieve at most two [16].…”

Section: A Foundationsmentioning

confidence: 99%

Scalable data management: NoSQL data stores in research and practice

Gessert

Ritter

2016

2016 IEEE 32nd International Conference on Data Engineering (ICDE)

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The unprecedented scale at which data is consumed and generated today has shown a large demand for scalable data management and given rise to non-relational, distributed "NoSQL" database systems. Two central problems triggered this process: 1) vast amounts of user-generated content in modern applications and the resulting requests loads and data volumes 2) the desire of the developer community to employ problemspecific data models for storage and querying. To address these needs, various data stores have been developed by both industry and research, arguing that the era of one-size-fits-all database systems is over. The heterogeneity and sheer amount of these systems -now commonly referred to as NoSQL data storesmake it increasingly difficult to select the most appropriate system for a given application. Therefore, these systems are frequently combined in polyglot persistence architectures to leverage each system in its respective sweet spot. This tutorial gives an in-depth survey of the most relevant NoSQL databases to provide comparative classification and highlight open challenges. To this end, we analyze the approach of each system to derive its scalability, availability, consistency, data modeling and querying characteristics. We present how each system's design is governed by a central set of trade-offs over irreconcilable system properties. We then cover recent research results in distributed data management to illustrate that some shortcomings of NoSQL systems could already be solved in practice, whereas other NoSQL data management problems pose interesting and unsolved research challenges.

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“…RELATED WORK a) Scalable Consistent Databases: Recent years have seen a surge of progress in the development of scalable object stores that support transactions. Some systems such as [14], [15], [16], [17], [18] [20] use lock chains and assume transactions are known in advance. These methods scale well and often allow databases to accept loads similar to those handled by non-transactional databases.…”

Section: B Realistic Workloadsmentioning

confidence: 99%

Cache Serializability: Reducing Inconsistency in Edge Transactions

Eyal

Birman

Renesse

2015

2015 IEEE 35th International Conference on Distributed Computing Systems

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Read-only caches are widely used in cloud infrastructures to reduce access latency and load on backend databases. Operators view coherent caches as impractical at genuinely large scale and many client-facing caches are updated in an asynchronous manner with best-effort pipelines. Existing solutions that support cache consistency are inapplicable to this scenario since they require a round trip to the database on every cache transaction. Existing incoherent cache technologies are oblivious to transactional data access, even if the backend database supports transactions. We propose T-Cache, a novel caching policy for read-only transactions in which inconsistency is tolerable (won't cause safety violations) but undesirable (has a cost). T-Cache improves cache consistency despite asynchronous and unreliable communication between the cache and the database. We define cache-serializability, a variant of serializability that is suitable for incoherent caches, and prove that with unbounded resources T-Cache implements this new specification. With limited resources, T-Cache allows the system manager to choose a trade-off between performance and consistency. Our evaluation shows that T-Cache detects many inconsistencies with only nominal overhead. We use synthetic workloads to demonstrate the efficacy of T-Cache when data accesses are clustered and its adaptive reaction to workload changes. With workloads based on the real-world topologies, T-Cache detects 43-70% of the inconsistencies and increases the rate of consistent transactions by 33-58%.Comment: Ittay Eyal, Ken Birman, Robbert van Renesse, "Cache Serializability: Reducing Inconsistency in Edge Transactions," Distributed Computing Systems (ICDCS), IEEE 35th International Conference on, June~29 2015--July~2 201

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Scalable atomic visibility with RAMP transactions

Cited by 81 publications

References 35 publications

G-Dur

G-Dur

Scalable data management: NoSQL data stores in research and practice

Cache Serializability: Reducing Inconsistency in Edge Transactions

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