Remaining in Control of the Impact of Schema Evolution in NoSQL Databases

During the development of NoSQL-backed software, the database schema evolves naturally alongside the application code. Especially in agile development, new application releases are deployed frequently. Eventually, decisions have to be made regarding the migration of versioned legacy data which is persisted in the cloud-hosted production database. We address this schema evolution problem and present results by means of which software project stakeholders can manage the operative costs for schema evolution and adapt their software release strategy accordingly in order to comply with service-level agreements regarding the competing metrics of migration costs and latency. We clarify conclusively how schema evolution in NoSQL databases impacts these metrics while taking all relevant characteristics of migration scenarios into account. As calculating all combinatorics in the search space of migration scenarios by far exceeds computational means, we use a probabilistic Monte Carlo method of repeated sampling, serving as a well-established method to bring the complexity of schema evolution under control.