This paper surveys spatial database organization and modelling as it is becoming a crucial issue for an ever increasing number of geometric data manipulation systems. We are here interested in efficient representation and storage structures for rapid processing of large sets of geometric data, as required by robotics applications, Very Large Scale Integration (VLSI) layout design, cartography, Computer Aided Design (CAD), or geographic information systems (GIS), where frequent operations involve spatial reasoning over that data. Existing database systems lack expressiveness to store some kinds of information which are inherently present in a geometric reasoning process, such as metric information, e.g. proximity, parallelism; or topological information, e.g. inclusion, intersection, contiguity, crossing. Geometric databases (GDB) alleviate this problem by providing an explicit representation for the spatial layout of the world in terms of empty and occupied space, together with a complete description of each object in it. Access to the data is done in an associative manner, that is, by specifying values over some usually small (sub)set of attributes, e.g. the coordinates of physical space. Manipulating data in GDB systems involves often spatially localized operations, i.e., locations, and consequently objects, which are accessed in the present are likely to be accessed again in a near future; this locality of reference which Hegron  calls temporal coherence, is due mainly to real world physical constraints. Indeed if accesses are caused for example by a sensor module which inspects its surroundings, then it is reasonable to suppose that successive scanned territories are not very far apart.