iBLOB: Complex Object Management in Databases through Intelligent Binary Large Objects

Abstract

New emerging applications including genomic, multimedia, and geo-spatial technologies have necessitated the handling of complex application objects that are highly structured, large, and of variable length. Currently, such objects are handled using filesystem formats like HDF and NetCDF as well as the XML and BLOB data types in databases. However, some of these approaches are very application specific and do not provide proper levels of data abstraction for the users. Others do not support random updates or cannot manage large volumes of structured data and provide their associated operations. In this paper, we propose a novel two-step solution to manage and query application objects within databases. First, we present a generalized conceptual framework to capture and validate the structure of application objects by means of a type structure specification. Second, we introduce a novel data type called Intelligent Binary Large Object (iBLOB) that leverages the traditional BLOB type in databases, preserves the structure of application objects, and provides smart query and update capabilities. The iBLOB framework generates a type structure specific application programming interface (API) that allows applications to easily access the components of complex application objects. This greatly simplifies the ease with which new type systems can be implemented inside traditional DBMS.