With the advent of web 3.0, cloud and mobile technologies, data has evolved enormously in terms of quality and quantity to satisfy a variety of user needs. Managing and processing such large data efficiently and effectively is a major challenge to the information industry. Though conventional Database Management systems (DBMS) can support many applications, they are now unable to handle distinct types of data competently. Processing structured and unstructured data in conventional DBMS degrades system performance and results in inefficient storage utilization. In addition, cloud and mobile technologies offer various challenges to conventional databases in terms of performance and scalability. NoSQL services are based on highly scalable architecture and performance characteristics which are best suited for distributed services in cloud environment. However, when it comes to managing structured data, there is no match to the capabilities of conventional RDBMS technologies. Therefore, our approach is to design a distributed storage system using a combination of RDBMS and NoSQL databases to ensure optimal system performance and scalability. Our target system is a Radiology Information System (RIS), a component of e-Healthcare Information System (HIS) comprising of large amounts of structured, semi-structured and unstructured data. The RIS system will be hosted on a hybrid cloud where the private cloud is used to store the sensitive data of the patients and the public cloud is used to store the public data.
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