Service-oriented data denormalization for scalable web applications

Many techniques have been proposed to scale web applications. However, the data interdependencies between the database queries and transactions issued by the applications limit their efficiency. We claim that major scalability improvements can be gained by restructuring the web application data into multiple independent data services with exclusive access to their private data store. While this restructuring does not provide performance gains by itself, the implied simplification of each database workload allows a much more efficient use of classical techniques. We illustrate the data de-normalization process on three benchmark applications: TPC-W, RUBiS and RUBBoS. We deploy the resulting service-oriented implementation of TPC-W across an 85-node cluster and show that restructuring its data can provide at least an order of magnitude improvement in the maximum sustainable throughput compared to master-slave database replication, while preserving strong consistency and transactional properties.