DyVer: Dynamic Version Handling for Array Databases

Abstract

Array databases are important data management systems for scientific applications. In array databases, version handling is an important problem due to the no-overwrite feature of scientific data. Existing studies for optimizing data versioning in array databases are relatively simple, which either focus on minimizing storage sizes or improving simple version chains. In this paper, we focus on two challenges: (1) how to balance the tradeoff between storage size and query time for numerous version data, which may have derivative relationships with each other; (2) how to dynamically maintain this balance with continuously added new versions. To address the above challenges, this paper presents DyVer, a versioning framework for SciDB which is one of the most well-known array databases. DyVer includes two techniques, including an efficient storage layout optimizer to quickly reduce data query time under storage capacity constraint and a version segment technique to cope with dynamic version additions. We evaluate DyVer using real-world scientific datasets. Results show that DyVer can achieve up to 95% improvement on the average query time compared to state-of-the-art data versioning techniques under the same storage capacity constraint.