Consider a particle in a finite dimensional Euclidean space performing a Brownian motion with an instantaneous drift vector at every time point determined by the order in which the coordinates of its location can be arranged as a decreasing sequence. These processes appear naturally in a variety of areas from queueing theory, statistical physics, and economic modeling. One is generally interested in the spacings between the ordered coordinates under such a motion. For finite $n$, the invariant distribution of the vector of spacings can be completely described and is a function of the drift. We show, as $n$ grows to infinity, a curious phenomenon occurs. We look at a transformation of the original process by exponentiating the location coordinates and dividing them by their total sum. Irrespective of the drifts, under the invariant distribution, only one of three things can happen to the transformed values: either they all go to zero, or the maximum grows to one while the rest go to zero, or they stabilize and converge in law to some member of a two parameter family of random point processes. This family known as the Poisson-Dirichlet's appears in genetics and renewal theory and is well studied. The proof borrows ideas from Talagrand's analysis of Derrida's Random Energy Model of spin glasses. We also consider another alternative starting with a countable collection of Brownian motions. This countable model is related to the Harris model of elastic collisions and the discrete Ruzmaikina-Aizenmann model for competing particles. This is based on separate joint works with Sourav Chatterjee and Jim Pitman.