Given a set of n objects, each characterized by d attributes specified at m fixed time instances, we are interested in the problem of designing space efficient indexing structures such that a class of temporal range search queries can be handled efficiently. When , our problem reduces to the d-dimensional orthogonal search problem. We establish efficient data structures to handle several classes of the general problem. Our results include a linear size data structure that enables a query time of for one-sided queries when , where f is the number of objects satisfying the query. A similar result is shown for counting queries. We also show that the most general problem can be solved with a polylogarithmic query time using superlinear space data structures.