Database applications such as enterprise resource planning systems and customer relationship management systems are widely used software systems. Development and testing of database applications is difficult because the program execution depends on the persistent state stored in the database. In this paper we show that how versioning of the persistent data stored in the database can solve some critical problems in the development and testing of database applications can be solved by versioning the data stored in the database. Our solution framework is based on long transaction management, a well-researched branch of database systems. We also present empirical results that show the proposed framework's effectiveness in practice.

In this paper we present a more efficient record based caching model than the conventional page (disk block) based scheme. In a record caching model, individual records are stored together in a section of shared memory to form the cache. Traditional relational database systems have individual pages that are stored together in shared memory to form the cache and records are then extracted from these pages on demand. The record cache model has better memory utilization than the page model and also helps reduce overheads like page fetches/writes, page locks and code path.