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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.
We study here the impact of priorities on conflict resolution in inconsistent relational databases. We extend the framework of repairs and consistent query answers. We propose a set of postulates that an extended framework should satisfy and consider
We present a new approach to e-matching based on relational join; in particular, we apply recent database query execution techniques to guarantee worst-case optimal run time. Compared to the conventional backtracking approach that always searches the
A consistent query answer in an inconsistent database is an answer obtained in every (minimal) repair. The repairs are obtained by resolving all conflicts in all possible ways. Often, however, the user is able to provide a preference on how conflicts
Data analysis often involves comparing subsets of data across many dimensions for finding unusual trends and patterns. While the comparison between subsets of data can be expressed using SQL, they tend to be complex to write, and suffer from poor per
HRDBMS is a novel distributed relational database that uses a hybrid model combining the best of traditional distributed relational databases and Big Data analytics platforms such as Hive. This allows HRDBMS to leverage years worth of research regard