Many problems require working with data that varies in its structure and content. Likewise, many tools have been developed to deal with different kinds of this problem, e.g., schema evolution tools or data integration tools. However, these approaches address only the specific kind of variation in databases resulting in two problems: Some fail to address all users’ needs for their specific kind of variation and all fail to address the interaction of different kinds of variation in databases. For example, neither schema evolution nor data integration systems can manage the data variation when an integrated database evolves over time. In this paper, we define a generic framework that explicitly accounts for variation in databases. Thus, it captures variation in the structure and content of a database and allows queries to express variational information needs. Our framework adds expressiveness to databases since it can encode any kind of variation. We design and implement a variational database management system as an abstraction layer over a traditional relational database. Using previously developed use cases that show the feasibility of our framework, we demonstrate the performance of different approaches used in our system.