Data management is fundamental to data-centric embedded systems with high resources scarcity and heterogeneity. Existing data management systems are very complex and provide a multitude of functionality. Due to complexity and their monolithic architecture, tailoring these data management systems for data-centric embedded systems is tedious, cost-intensive, and error-prone. In order to cope with complexity of data management in such systems, we propose a different approach to DBMS architecture, called Cellular DBMS, that is inspired by biological systems. Cellular DBMS is a compound of multiple simpler DBMS, called DBMS Cells, that typically provide differing functionality(e.g., persistence storage, indexes, transactions, etc.). We illustrate how the software product line approach is useful to generate different individual DBMS cells from a commonest of features and how generated atomic DBMS cells can be used together for data management on data-centric embedded systems.