A current trend in database architecture is to provide ‘data blades’ or ‘data cartridges’ as ‘plug-in’ indexing methods to support new data types. The research project which gave rise to this paper aims to test the practicality of a diametrically opposite approach: the development of a new, generic indexing technology i.e. a single indexing technique capable of supporting a wide range of data types. We believe that BANG indexing [Fre87] is now a viable candidate for such a technology, as a result of a series of extensions and refinements, and fundamental improvements in worst-case characteristics made possible by recent theoretical advances EFre95, Fre97f. The task is therefore to test whether this single generalized technique can match the performance of several other specialized methods. This paper is devoted to the indexing of spatial extents. It describes a simple refinement of an earlier approach to spatial extent indexing based on a dud BANG representation, and compares its performance with that of the R*-tree. The results are surprising. In essence, they show that BANG indexing is able to match - and in many cases significantly surpass - the query performance of the R*-tree without incurring the heavy index optimization costs of the R*-tree. This leads to dramatic improvements in indexing times.