We will develop the basic software building blocks of the analysis in a computationally efficient manner by employing the parallelism in C/C++ programming, GPU and multiple cores. First the focus will be on methodologies for optimizing the server utilization the storage utilization. For that, we will employ practices and modules which integrates HPC, cloud, and big data technologies, for providing large-scale testbed for big data pipelines for accelerating data ingestion, transfer and processing. A large graph database management system, based on state-of-the-art technology, such as Neo4j will be deployed. The system will provide graph retrieval and similarity search operators. The efficiency on querying the datasets will be examined considering the various types of experiments, datasets and analysis requirements.