Periodicity mining is used for predicting different applications such as prediction,forcasting etc.It has several application in Timeseries databases.Several algorithms are present for detecting the periodicity.But most of the algorithm do not take into account the presence of noise or partial periodicity.Here we compare four different types of algorithm.Based on timewraping ,the first algorithm wraps the time axis to optimally remove the noise at various locations.The second algorithm can be viewed as a variation of the approximate string matching algorithm. The third algorithm is used for partial periodicity detection and in the fourth one periodic detection using suffix tree is done .This algorithms detects periodicity in noise and also detects partial periodicity .Here acomparison of three algorithms are done.