Latency-Redundancy Tradeoff in Distributed Read-Write Systems

TL;DR

This paper analyzes the tradeoff between read and write latency in distributed databases with redundant data storage, providing a quantitative model and practical guidelines for optimal redundancy levels.

Contribution

It introduces a mathematical model quantifying the latency tradeoff in distributed read-write systems and offers a closed-form approximation validated empirically.

Findings

The model accurately predicts latency tradeoffs across system parameters.

Redundancy levels can be optimized based on the derived approximation.

Guidelines for redundancy selection improve database performance management.

Abstract

Data is replicated and stored redundantly over multiple servers for availability in distributed databases. We focus on databases with frequent reads and writes, where both read and write latencies are important. This is in contrast to databases designed primarily for either read or write applications. Redundancy has contrasting effects on read and write latency. Read latency can be reduced by potential parallel access from multiple servers, whereas write latency increases as a larger number of replicas have to be updated. We quantify this tradeoff between read and write latency as a function of redundancy, and provide a closed-form approximation when the request arrival is Poisson and the service is memoryless. We empirically show that this approximation is tight across all ranges of system parameters. Thus, we provide guidelines for redundancy selection in distributed databases.