An Associator implements a multi-dimensional finite metric space, where each dimension is represented by one single unsigned byte. An Associator organises the nodes (or vertices) by building an incremental proximity graph (IPG) with the manhattan distance metric (L1 norm). This IPG is built during insertion and allows efficient ANN (Approximate Nearest Neighbour) searches even on very large datasets.