Managing Variability in Relational Databases by VDBMS

TL;DR

This paper introduces a formal framework and a management system for handling variability in relational databases, enabling effective querying across different database variants.

Contribution

It defines variational databases and queries, and develops a variational database management system to manage and query database variability efficiently.

Findings

Successfully generated variational databases from real-world data

Implemented a variational query system and evaluated its performance

Demonstrated effective management of database variability

Abstract

Variability inherently exists in databases in various contexts which creates database variants. For example, variants of a database could have different schemas/content (database evolution problem), variants of a database could root from different sources (data integration problem), variants of a database could be deployed differently for specific application domain (deploying a database for different configurations of a software system), etc. Unfortunately, while there are specific solutions to each of the problems arising in these contexts, there is no general solution that accounts for variability in databases and addresses managing variability within a database. In this paper, we formally define variational databases (VDBs) and statically-typed variational relational algebra (VRA) to query VDBs---both database and queries explicitly account for variation. We also design and implement variational database management system (VDBMS) to run variational queries over a VDB effectively and efficiently. To assess this, we generate two VDBs from real-world databases in the context of software development and database evolution with a set of experimental queries for each.