The dangers of replication and a solution
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Asymptotic analysis of multiclass closed queueing networks: multiple bottlenecks
Performance Evaluation
Ganymed: scalable replication for transactional web applications
Proceedings of the 5th ACM/IFIP/USENIX international conference on Middleware
Adaptive middleware for data replication
Proceedings of the 5th ACM/IFIP/USENIX international conference on Middleware
Proceedings of the 1st ACM SIGOPS/EuroSys European Conference on Computer Systems 2006
C-JDBC: flexible database clustering middleware
ATEC '04 Proceedings of the annual conference on USENIX Annual Technical Conference
Statistical analysis of simulation output: state of the art
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Middleware-based database replication: the gaps between theory and practice
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
An Observation-Based Approach to Performance Characterization of Distributed n-Tier Applications
IISWC '07 Proceedings of the 2007 IEEE 10th International Symposium on Workload Characterization
Experimental evaluation of N-tier systems: Observation and analysis of multi-bottlenecks
IISWC '09 Proceedings of the 2009 IEEE International Symposium on Workload Characterization (IISWC)
CloudXplor: a tool for configuration planning in clouds based on empirical data
Proceedings of the 2010 ACM Symposium on Applied Computing
Automated control for elastic n-tier workloads based on empirical modeling
Proceedings of the 8th ACM international conference on Autonomic computing
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The performance evaluation of database servers in N-tier applications is a serious challenge due to requirements such as non-stationary complex workloads and global consistency management when replicating database servers. We conducted an experimental evaluation of database server scalability and bottleneck identification in N-tier applications using the RUBBoS benchmark. Our experiments are comprised of a full scale-out mesh with up to nine database servers and three application servers. Additionally, the fourtier system was run in a variety of configurations, including two database management systems (MySQL and PostgreSQL), two hardware node types (normal and low-cost), and two database replication techniques (C-JDBC and MySQL Cluster). In this paper we present the analysis of results generated with a read-intensive interaction pattern (browse-only workload) in the client emulator. These empirical data can be divided into two kinds. First, for a relatively small number of servers, we find simple hardware resource bottlenecks. Consequently, system throughput increases with an increasing number of database (and application) servers. Second, when sufficient hardware resources are available, non-obvious database related bottlenecks have been found that limit system throughput. While the first kind of bottlenecks shows that there are similarities between database and application/web server scalability, the second kind of bottlenecks shows that database servers have significantly higher sophistication and complexity that require in-depth evaluation and analysis.