Improving Performance in Replicated Databases through Relaxed Coherency

Applications in finance and telecommunications (intelligent network, network management, mobile computing) cause renewed interest in distributed and replicated data management. Since synchronous update of replicated data is experienced to degrade distributed systems performance substantially, relaxing the requirement of coherency (mutual consistency) has become a favorable approach to achieve high performance in replicated databases. In this paper we present formal concepts for specifying relaxed coherency which allows to calculate an independent measure of relaxation, called + coherency index. We incorporate this metric into a detailed analytical queueing model which emphasizes on the quality of replication to evaluate the impact of relaxed coherency on the performance of replicated databases. The model considers response time, throughput, scalability and network traffic as performance criteria. As it turns out, performance improvements through relaxed coherency depend significantly on various system parameters. We closely examine the trade off between consistency and performance, and show that in many situations a slight relaxation of coherency can increase performance remarkably. Finally, we verify these results by benchmarking an implementation of relaxed coherency.