In the last 20 years, cloud and grid computing have become paradigms for accessing and managing geographically distributed content across a network. While these paradigms are very relevant, they bring a series of new challenges to security, performance, and scalability.

This volume is a collection of contributions from international experts. It presents an overview of grid and cloud database management, with topics ranging from standards and specifications to research projects and case studies.

The book is divided into four sections. The first (short) section is on specifications, open standards, and their relationship. It describes and discusses in detail data access and integration standards for distributed environments developed by the Database Access and Integration Services (DAIS) Working Group and the Open Cloud Computing Interface (OCCI) family of specifications.

Section 2 presents three research efforts on grid database management. The University of Salento’s Grid Relational Catalog (GRelC) project and the Open Grid Services Architecture--Data Access and Integration (OGSA-DAI) are presented and discussed in terms of performance, security, and interoperability. The third initiative discussed in this section is DASCOSA-DB, a peer-to-peer (P2P)-based grid database system architecture for data-intensive applications in dynamic environments developed by the Norwegian University of Science and Technology. Its features are discussed in detail; however, since performance and scalability are just commented on, readers are directed to earlier papers, which are referenced in the text, to learn more.

Section 3 covers specific aspects of cloud and grid database management. The section first focuses on database aspects, such as access control and trustiness, for resource management through innovative security techniques, dirty data management, virtualization, and column-oriented database systems. Subsequently, more general management issues are described and commented on, such as a space situational awareness application and a cloud-based distributed data mining environment. A chapter dedicated to the management of data-intensive workloads in the cloud contains an interesting classification and comparison of provisioning techniques.

Finally, Section 4 presents scientific case studies in which cloud and grid databases are used effectively. The first case study is dedicated to the management and analysis of genomic data using high-performance computing (HPC) and clouds, and the second to satellite data processing and management for disaster monitoring using grid techniques. The two last cases are about “interactive analysis and high-resolution mapping of environmental and remote sensing data,” and the distributed storage of large-scale multidimensional electroencephalogram data.

I recommend this book not only as a technical reference for researchers, students, programmers, and systems engineers, but also as an introduction to cloud and grid computing database paradigms.