Cloud computing is increasingly important, with the industry moving towards outsourcing computational resources as a means to reduce investment and management costs, while improving security, dependability and performance. Cloud operators use multi-tenancy, by grouping virtual machines (VMs) into a few physical machines (PMs), to pool computing resources, thus offering elasticity to clients. Although cloud-based fault tolerance schemes impose communication and synchronization overheads, the cloud offers excellent facilities for critical applications, as it can host varying numbers of replicas in independent resources. Given these contradictory forces, determining whether the cloud can host elastic critical services is a major research question. We address this challenge from the perspective of a standard three-tiered system with relational data. We propose to tolerate Byzantine faults using groups of replicas placed on distinct physical machines, as a means to avoid exposing applications to correlated failures. To improve the scalability of our system, we divide data to enable parallel accesses. Using a realistic setup, this setting can reach speedups largely exceeding the number of partitions. Even for a wide variation of the load, the system preserves latency and throughput within reasonable bounds. We believe that the elasticity we observe demonstrates the feasibility of tolerating Byzantine faults in a cloud-based server using a relational database.