Semantics-Driven Optimistic Data Replication

Optimistic data replication is an important enabling technology for high availability and scalability, but the disadvantage is that it can only guarantee eventual consistency. Inconsequence, apps might observe stale data and write conflicts. In practice, optimistic data replication is usually part of data base systems that implement detection and resolution of conflicts with purely syntactic techniques. On the downside, this can lead to conflicts that are impossible to detect and resolve correctly by using the database framework only, ultimately resulting in concurrency anomalies. In order to avoid concurrency anomalies, developers are forced to use error-prone workarounds, there by increasing application complexity significantly. An alternative to using existing database replication would be to implement a custom solution tailored to the application semantics that could minimize the occurrence of write conflicts and concurrency anomalies. However, the realization of custom solutions driven by application semantics is very difficult in practice, due to the complexity of concurrency control in distributed systems. In this position paper we demonstrate practical problems related to state of-the-practice optimistic data replication and motivate the need for semantics-driven solutions. Our research aims at simplifying the development of custom solutions by delivering a frame workfor semantics-driven optimistic data replication. This frame work consists of a technical part and accompanying concepts for the design of extended domain models optimized for optimistic data replication and conflict minimization.