ScienceDirect 2013 AASRI Conference on Parallel and Distributed Computing and Systems 5-Layered Architecture of Cloud Database Management System

Abstract Cloud Database Management System is a new emerging concept recently introduced in the world. In Cloud the concept of Standard architecture of Cloud Database Management System is not yet been implemented. In this paper we are proposing a framework for 5-layered architecture in cloud database management system. First layer introduced is the External Layer, this layer is closest to the user, in which manageability, providing transparency and security are the important issue that should be considered. Second layer is the Conceptual Middleware Layer, as there are heterogeneous databases and clouds are available in the market, so here interoperability is the major issue. Third layer is the Conceptual Layer in which programming techniques, transaction management, query processing and optimization are the issues that should be considered. Forth layer is the Physical Middleware Layer, as there are various platforms available so here also, interoperability between various platforms are the biggest issue and the last layer is the Physical Layer in which how data can be stored so that it can be easily accessible without so much overhead so here data security, storage, backup, load balancing, partitioning, scaling, elasticity, fault tolerance and replication are the important issues that should be considered

ScienceDirect 2013 AASRI Conference on Parallel and Distributed Computing and Systems 5-Layered Architecture of Cloud Database Management System

Abstract Cloud Database Management System is a new emerging concept recently introduced in the world. In Cloud the concept of Standard architecture of Cloud Database Management System is not yet been implemented. In this paper we are proposing a framework for 5-layered architecture in cloud database management system. First layer introduced is the External Layer, this layer is closest to the user, in which manageability, providing transparency and security are the important issue that should be considered. Second layer is the Conceptual Middleware Layer, as there are heterogeneous databases and clouds are available in the market, so here interoperability is the major issue. Third layer is the Conceptual Layer in which programming techniques, transaction management, query processing and optimization are the issues that should be considered. Forth layer is the Physical Middleware Layer, as there are various platforms available so here also, interoperability between various platforms are the biggest issue and the last layer is the Physical Layer in which how data can be stored so that it can be easily accessible without so much overhead so here data security, storage, backup, load balancing, partitioning, scaling, elasticity, fault tolerance and replication are the important issues that should be considered

UDBMS : Road to Unification for Multi-model Data Management

One of the greatest challenges in big data management is the “Variety” of the data. The data may be presented in various types and formats: structured, semi-structured and unstructured. For instance, data can be modeled as relational, key-value, and graph models. Having a single data platform for managing both well-structured data and NoSQL data is beneficial to users; this approach reduces significantly integration, migration, development, maintenance, and operational issues. Therefore, a challenging research work is how to develop an efficient consolidated single data management platform covering both NoSQL and relational data to reduce integration issues, simplify operations, and eliminate migration issues. In this paper, we envision novel principles and technologies to handle multiple models of data in one unified database system, including model-agnostic storage, unified query processing and indexes, in-memory structures and multi-model transactions. We discuss our visions as well as present research challenges that we need to address.Peer reviewe