Attaining Workload Scalability and Strong Consistency for Replicated Databases with Hihooi

Georgiou, Michael A.; Panayiotou, Michael; Odysseos, Lambros; Paphitis, Aristodemos; Sirivianos, Michael; Herodotou, Herodotos

doi:10.1145/3448016.3452746

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…The second large group of recent research activities (see Table 2) puts forward (i) new data models suitable for efficient distributed across multiple nodes [29-30]; (ii) new consistency models [40-46], (iii) consistency control algorithms and consensus quorum protocols [31][32][33][34][35][36][37][38][39], and (iv) techniques for data replications and strategies for replica placement [47][48][49][50][51][52][53][54][55].…”

Section: A Survey Of Recent Research Work Studying Distributed Data S...mentioning

confidence: 99%

Consistency issue and related trade-offs in distributed replicated systems and databases: a review

Ahmed¹,

Karpenko²,

Tarasyuk³

et al. 2023

reks

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Distributed replicated databases play a crucial role in modern computer systems enabling scalable, fault-tolerant, and high-performance data management. However, achieving these qualities requires resolving a number of trade-offs between various properties during system design and operation. This paper reviews trade-offs in distributed replicated databases and provides a survey of recent research papers studying distributed data storage. The paper first discusses a compromise between consistency and latency that appears in distributed replicated data storages and directly follows from CAP and PACELC theorems. Consistency refers to the guarantee that all clients in a distributed system observe the same data at the same time. To ensure strong consistency, distributed systems typically employ coordination mechanisms and synchronization protocols that involve communication and agreement among distributed replicas. These mechanisms introduce additional overhead and latency and can dramatically increase the time taken to complete operations when replicas are globally distributed across the Internet. In addition, we study trade-offs between other system properties including availability, durability, cost, energy consumption, read and write latency, etc. In this paper we also provide a comprehensive review and classification of recent research works in distributed replicated databases. Reviewed papers showcase several major areas of research, ranging from performance evaluation and comparison of various NoSQL databases to suggest new strategies for data replication and putting forward new consistency models. In particular, we observed a shift towards exploring hybrid consistency models of causal consistency and eventual consistency with causal ordering due to their ability to strike a balance between operations ordering guarantees and high performance. Researchers have also proposed various consistency control algorithms and consensus quorum protocols to coordinate distributed replicas. Insights from this review can empower practitioners to make informed decisions in designing and managing distributed data storage systems as well as help identify existing gaps in the body of knowledge and suggest further research directions.

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Section: A Survey Of Recent Research Work Studying Distributed Data S...mentioning

confidence: 99%

Consistency issue and related trade-offs in distributed replicated systems and databases: a review

Ahmed¹,

Karpenko²,

Tarasyuk³

et al. 2023

reks

View full text Add to dashboard Cite

show abstract

“…Elastic data warehousing can be defined as a process that enables a database to adapt to the growth in data rate, data volume and concurrency without affecting the overall performance. Such a data warehouse plays a vital role in providing dedicated resources for undergoing different business operations within the organization and managing all the tasks [1]. In this digital world, data warehousing has been advanced with the help of advanced and modern technologies like clout-native technologies that are helpful in managing workloads effectively and efficiently.…”

Section: Introductionmentioning

confidence: 99%

Elastic Data Warehousing: Adapting To Fluctuating Workloads With Cloud-Native Technologies

Ahmadi

2023

JKLST

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This research focuses on the development of elastic data warehousing while adapting to changing workloads with the help of cloud-based technologies. The traditional methods of data warehousing need innovative and creative strategies in order to improve their efficiency. Thus, this research focuses on analyzing innovative methods which can improve the future of data warehousing, such as machine learning, encryption, artificial intelligence, etc. Moreover, the study also focuses on specific industries that require customized solutions to data warehousing. These include the manufacturing, finance, and healthcare industries. The study uses qualitative data gained through a comprehensive review of literature. The findings reveal a great level of significance of modern data warehousing techniques that assist in improving the overall efficiency of traditional methods

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Elastic Data Warehousing: Adapting To Fluctuating Workloads With Cloud-Native Technologies

Ahmadi

2024

Preprint

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Attaining Workload Scalability and Strong Consistency for Replicated Databases with Hihooi

Cited by 3 publications

References 13 publications

Consistency issue and related trade-offs in distributed replicated systems and databases: a review

Consistency issue and related trade-offs in distributed replicated systems and databases: a review

Elastic Data Warehousing: Adapting To Fluctuating Workloads With Cloud-Native Technologies

Elastic Data Warehousing: Adapting To Fluctuating Workloads With Cloud-Native Technologies

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