Grid computing technologies provide mechanisms that allow the seamless sharing of distributed and heterogeneous resources, such as supercomputers, storage systems, and data sources, in a large-scale and dynamic environment. Research works in data grids have generally focused on applications where data resources are stored in files. However, many scientific applications are highly dependent on database management systems for organizing and storing their data. This stresses the need for developing techniques that enable the sharing of and access to massively distributed, heterogeneous, and autonomous databases created and managed independently by several research institutions. In this paper, we address this issue and propose GriDB, a database sharing technique that has the following desirable characteristics: (1) it supports data indexing at a finer granularity than the file level, enabling content-based search and access; (2) it allows data sharing without a globally shared schema; (3) it is distinguished by its peer-to-peer flavor, making it highly scalable, auto-configurable, and fully decentralized with no need to centralized or dedicated servers.