µDatabase: A Toolkit for Constructing Memory Mapped Databases

The main objective of this work was an efficient methodology for constructing low-level database tools that are built around a single-level store implemented using memory mapping. The methodology allowed normal programming pointers to be stored directly onto secondary storage, and subsequently retrieved and manipulated by other programs without the need for relocation, pointer swizzling or reading all the data. File structures for a database, e.g. a B-Tree, built using this approach are significantly simpler to build, test, and maintain than traditional file structures. All access methods to the file structure are statically type-safe and file structure definitions can be generic in the type of the record and possibly key(s) stored in the file structure, which affords significant code reuse. An additional design requirement is that multiple file structures may be simultaneously accessible by an application. Concurrency at both the front end (multiple accessors) and the back end (file structure partitioned over multiple disks) are possible. Finally, experimental results between traditional and memory mapped files structures show that performance of a memory mapped file structure is as good or better than the traditional approach.