Volumes of data are exploding in both scientific and commercial domains. Data mining techniques that extract information from the huge amount of data have become popular in many applications. Algorithms are designed to analyze those volumes of data automatically inefficient ways so that users can grasp the intrinsic knowledge latent in the data. Clustering is important in data analysis and data mining applications. Clustering is a division of data into a group of similar objects. Each group called a cluster consists of objects that are similar between themselves and dissimilar between comparing to objects of other groups. This paper is aimed to study of all the parallel data mining algorithms based on partition.