Paper Info
Title
In-memory transaction processing: efficiency and scalability considerations
Abstract
Traditional disk-resident OLTP systems were mainly designed for computers with relatively small memory. Driven by the advance of hardware, OLTP systems need to be redesigned for larger memory and multi-core environments. Compared to disk-resident systems, in-memory systems have significant performance advantages, from the perspectives of both transaction throughput and query latency. Their performance is no longer limited by disk I/Os. Instead, the efficiency and scalability over multi-core CPUs become more important. In this paper, we survey and summarize a wide spectrum of design and implementation considerations that may affect the efficiency or scalability of an in-memory OLTP system. These considerations are concerned with most of the main components of databases, including concurrency control, logging, indexing and transaction compilation. For each of the components, we provide some in-depth analysis based on recent research works. This survey also aims to provide some guidance for designing or implementing high-performance in-memory OLTP systems.
Year
DOI
Venue
2019
10.1007/s10115-019-01340-7
Knowledge and Information Systems
Keywords
Field
DocType
Database system, Transaction processing, In-memory database, Concurrency control
Transaction processing,Data mining,Concurrency control,Computer science,Online transaction processing,In-memory database,Search engine indexing,Throughput,Database transaction,Distributed computing,Scalability
Journal
Volume
Issue
ISSN
61
3
0219-3116
Citations 
PageRank 
References 
0
0.34
87
Authors
5
Name
Order
Citations
PageRank
Huiqi Hu1796.22
Xuan Zhou223.78
Tao Zhu38214.36
Weining Qian4106481.09
Aoying Zhou52632238.85