Hihooi: A Database Replication Middleware for Scaling Transactional Databases Consistently

Georgiou, Michael A.; Paphitis, Aristodemos; Sirivianos, Michael; Herodotou, Herodotos

doi:10.1109/tkde.2020.2987560

Cited by 5 publications

(2 citation statements)

References 40 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

“…Database data extraction [6] is divided into two types in terms of data extraction methods, one is based on the query, and the other is based on the log. The source database is accessed through API based on the query, and the query obtains the latest data.…”

Section: Data Extractionmentioning

confidence: 99%

Flink-based Heterogeneous Database Synchronization Adapter Design

Xiong

Zhang

2022

J. Phys.: Conf. Ser.

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The existing data synchronization scheme can satisfy the data synchronization between homogeneous table databases. Still, it restricts the table structures that can be synchronized and cannot solve the table heterogeneous database synchronization problem. In this paper, based on the existing data synchronization tools, we analyze the key problems in data synchronization, such as data type differences, data storage differences, data expression differences, etc. To design a synchronization model for these problems, this paper investigates the implementation of Flink CDC and the design idea of the Binlog model and designs a highly available and easily scalable heterogeneous database synchronization model by combining the actual data synchronization scenarios and traditional synchronization ideas.

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