In this paper we propose SparkBLAST, a parallelization of BLAST that employs cloud computing for the provisioning of computational resources and Apache Spark as the coordination framework. SparkBLAST outperforms CloudBLAST, a Hadoop-based implementation, in speedup, efficiency and scalability in a highly distributed cloud platform. The superior performance of SparkBLAST is mainly due to the in-memory operations available through the Spark framework, consequently reducing the number of local I/O operations required for distributed BLAST processing.