Current advancements in next generation sequencing technology have made possible to sequence whole genome but assembling a large number of short reads is still a big challenge. In this article, we present the comparative study of seven assemblers namely ABySS, Velvet, Edena, SGA, Ray, SSAKE and Perga, using seven paired-end and eight single-end prokaryotic datasets from Illumina platform. Results showed that in case of single-end datasets, Velvet and ABySS outperformed all seven assemblers with comparatively low assembling time and high genome fraction. The Velvet consumed the least amount of memory than any other assembler. In case of paired-end datasets, Velvet consumed least amount of time and produced high genome fraction after ABySS and Ray. In term of low memory usage, SGA and Edena outperformed all seven assemblers. The Ray also showed good genome fraction, however extremely high assembling time consumed by the Ray might make it prohibitively slow on larger datasets of single and paired-end data. Our study would provide assistance to the biologists and bioinformaticians for selecting the suitable assembler according to their datasets. This will also help the developers to upgrade or develop a new assembler for de novo assembling.