Performance Comparison of Three Modern DBMS Architectures

Alexios Delis; Nick Roussopoulos

doi:10.1109/32.214830

Performance Comparison of Three Modern DBMS Architectures

Alexios Delis, Nick Roussopoulos

Computer Science

Research output: Contribution to journal › Article › peer-review

Abstract

The introduction of powerful workstations connected through local area networks (LAN’s) inspired new DBMS architectures that offer high performance characteristics. In this paper, we examine three such software architecture configurations: Client-Server (CS), RAD-UNIFY® type of DBMS (RU), and Enhanced Client-Server (ECS). Their specific functional components and design rationales are discussed. We use three simulation models to provide a performance comparison under different job workloads. Our simulation results show that the RU almost always performs slightly better than the CS, especially under light workloads, and that ECS offers significant performance improvement over both CS and RU. Under reasonable update rates, the ECS over CS (or RU) performance ratio is almost proportional to the number of participating clients (for less than 32 clients). We also examine the impact of certain key parameters on the performance of the three architectures and finally show that ECS is more scalable that the other two.

Original language	English (US)
Pages (from-to)	120-138
Number of pages	19
Journal	IEEE Transactions on Software Engineering
Volume	19
Issue number	2
DOIs	https://doi.org/10.1109/32.214830
State	Published - Feb 1993

Keywords

Client-Server DBMS architectures
data caching
DBMS architecture modeling
incremental database operations
performance analysis

ASJC Scopus subject areas

Software

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title = "Performance Comparison of Three Modern DBMS Architectures",

abstract = "The introduction of powerful workstations connected through local area networks (LAN{\textquoteright}s) inspired new DBMS architectures that offer high performance characteristics. In this paper, we examine three such software architecture configurations: Client-Server (CS), RAD-UNIFY{\textregistered} type of DBMS (RU), and Enhanced Client-Server (ECS). Their specific functional components and design rationales are discussed. We use three simulation models to provide a performance comparison under different job workloads. Our simulation results show that the RU almost always performs slightly better than the CS, especially under light workloads, and that ECS offers significant performance improvement over both CS and RU. Under reasonable update rates, the ECS over CS (or RU) performance ratio is almost proportional to the number of participating clients (for less than 32 clients). We also examine the impact of certain key parameters on the performance of the three architectures and finally show that ECS is more scalable that the other two.",

keywords = "Client-Server DBMS architectures, data caching, DBMS architecture modeling, incremental database operations, performance analysis",

author = "Alexios Delis and Nick Roussopoulos",

note = "Funding Information: Manuscript received November 11, 1991; revised October 2, 1992. This research was sponsored partially by the National Science Foundation under Grant IRI-8719458, by the Air Force Office of Scientific Research Grant AFOSR-89-0303, and by the University of Maryland Institute for Advanced Computer Studies (UMIACS). Recommended by Matthias Jarke. The authors are with the Institute for Advanced Computer Studies and Computer Science Department, University of Maryland, College Park, MD 20742. IEEE Log Number 9206641.",

year = "1993",

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doi = "10.1109/32.214830",

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PY - 1993/2

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N2 - The introduction of powerful workstations connected through local area networks (LAN’s) inspired new DBMS architectures that offer high performance characteristics. In this paper, we examine three such software architecture configurations: Client-Server (CS), RAD-UNIFY® type of DBMS (RU), and Enhanced Client-Server (ECS). Their specific functional components and design rationales are discussed. We use three simulation models to provide a performance comparison under different job workloads. Our simulation results show that the RU almost always performs slightly better than the CS, especially under light workloads, and that ECS offers significant performance improvement over both CS and RU. Under reasonable update rates, the ECS over CS (or RU) performance ratio is almost proportional to the number of participating clients (for less than 32 clients). We also examine the impact of certain key parameters on the performance of the three architectures and finally show that ECS is more scalable that the other two.

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