Main Memory Database Recovery

Author:

Magalhaes Arlino1,Monteiro Jose Maria2,Brayner Angelo2

Affiliation:

1. Federal University of Ceara/Federal University of Piaui, Piaui, Brazil

2. Federal University of Ceara, Ceara, Brazil

Abstract

Many of today’s applications need massive real-time data processing. In-memory database systems have become a good alternative for these requirements. These systems maintain the primary copy of the database in the main memory to achieve high throughput rates and low latency. However, a database in RAM is more vulnerable to failures than in traditional disk-oriented databases because of the memory volatility. DBMSs implement recovery activities (logging, checkpoint, and restart) for recovery proposes. Although the recovery component looks similar in disk- and memory-oriented systems, these systems differ dramatically in the way they implement their architectural components, such as data storage, indexing, concurrency control, query processing, durability, and recovery. This survey aims to provide a thorough review of in-memory database recovery techniques. To achieve this goal, we reviewed the main concepts of database recovery and architectural choices to implement an in-memory database system. Only then, we present the techniques to recover in-memory databases and discuss the recovery strategies of a representative sample of modern in-memory databases.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. General-purpose Asynchronous Periodic Checkpointing in Hybrid Memory;Proceedings of the 52nd International Conference on Parallel Processing;2023-08-07

2. Data backup policies with failure-oblivious computing in reliability theory;Annals of Operations Research;2022-09-03

3. High-availability clusters: A taxonomy, survey, and future directions;Journal of Systems and Software;2022-05

4. Query Dictionary for Frequent Non-Indexed Queries in HTAP Databases;IEEE Access;2022

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