Data Mining as an area of computer science has been gaining enormous importance in various fields of business, spatial planning and predictive analysis. Clustering techniques are application tools to analyze stored data in various fields. It is a process to partition meaningful data into useful clusters which can be understandable and has analytical value. In the present paper after giving a brief outlook of data mining and clustering techniques, we have made a comparative study of various partitioning algorithms so as to study their worth at a level playing field. The analysis shows that not all partitions algorithms are efficient to handle large datasets. The exploration of partitioning algorithms opens new vistas for further development and research.