Towards Auto-Scaling Existing Transactional Databases with Strong Consistency

Abstract

Existing relational database systems often suffer from rapid increases or significant variability of transactional workloads but lack support for scalability or elasticity. Database replication has been employed to scale workload performance but past approaches make various performance versus consistency tradeoffs and typically lack the mechanisms and policies for dynamically adding and removing replicas. This paper presents Hihooi, a replication-based middleware system that is able to achieve scalability, strong consistency, and elasticity for existing transactional databases. These features are enabled by (i) a novel replication algorithm for propagating database modifications asynchronously and consistently to all replicas at high speeds, and (ii) a new routing algorithm for directing incoming transactions to consistent replicas. Our experimental evaluation validates the high scalability and elasticity benefits offered by Hihooi, which form the key ingredients towards a truly auto-scaling system.