In order to evaluate the performance and the benefits of SparkBLAST, we present two experiments. The first experiment was executed in the Google Cloud, and the second experiment executed in the Microsoft Azure platform. Both experiments executed with 1, 2, 4, 8, 16, 32, and 64 virtual machines as computing nodes for scalability measurement. For the sake of comparison, each experiment was executed on SparkBLAST and on CloudBLAST. The later is a Hadoop based tool designed to support high scalability on clusters and cloud environments. For the experiments, we used Spark 1.6.1 to execute SparkBLAST on both cloud environments. To execute CloudBLAST, we used Hadoop 2.4.1 on the Google Cloud, and Hadoop 2.5.2 on Azure Cloud. In any case, we configures YARN as the resource scheduler, since our experiments focus on performance. Further details on the experimental setup will be provided in the results section.