Latency Bounding by Trading off Consistency in NoSQL Store: A Staging and Stepwise Approach

TL;DR

This paper introduces dConssandra, a NoSQL store that allows users to specify latency bounds for data operations by trading off consistency, using a staged replication strategy to dynamically control latency and consistency levels.

Contribution

dConssandra extends Cassandra with a staged replication approach enabling dynamic latency bounds and adjustable consistency levels based on user-specified constraints.

Findings

Latency is effectively bounded by user-specified constraints.

Higher write latency bounds improve reading of the latest data.

Higher read latency bounds yield more recent data retrieval.

Abstract

Latency is a key service factor for user satisfaction. Consistency is in a trade-off relation with operation latency in the distributed and replicated scenario. Existing NoSQL stores guarantee either strong or weak consistencies but none provides the best consistency based on the response latency. In this paper, we introduce dConssandra, a NoSQL store enabling users to specify latency bounds for data access operations. dConssandra dynamically bounds data access latency by trading off replica consistency. dConssandra is based on Cassandra. In comparison to Cassandra's implementation, dConssandra has a staged replication strategy enabling synchronous or asynchronous replication on demand. The main idea to bound latency by trading off consistency is to decompose the replication process into minute steps and bound latency by executing only a subset of these steps. dConssandra also implements a different in-memory storage architecture to support the above features. Experimental results for dConssandra over an actual cluster demonstrate that (1) the actual response latency is bounded by the given latency constraint; (2) greater write latency bounds lead to a lower latency in reading the latest value; and, (3) greater read latency bounds lead to the return of more recently written values.