Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed

Towards an open cloud marketplace: vision and first steps

As one of the most promising, emerging concepts in Information Technology (IT), cloud computing is transforming how IT is consumed and managed; yielding improved cost efficiencies, and delivering flexible, on-demand scalability by reducing computing infrastructures, platforms, and services to commodities acquired and paid-for on-demand through a set of cloud providers. Today, the transition of cloud computing from a subject of research and innovation to a critical infrastructure is proceeding at an incredibly fast pace. A potentially dangerous consequence of this speedy transition to practice is the premature adoption, and ossification, of the models, technologies, and standards underlying this critical infrastructure. This state of affairs is exacerbated by the fact that innovative research on production-scale platforms is becoming the purview of a small number of public cloud providers. Specifically, the academic research communities are effectively excluded from the opportunity to contribute meaningfully to the evolution not to mention innovation and healthy mutation of cloud computing technologies. As the dependence on our society and economy on cloud computing increases, so does the realization that the academic research community cannot be shut out from contributing to the design and evolution of this critical infrastructure. In this article we provide an alternative vision that of an Open Cloud eXchange (OCX) a public cloud marketplace, where many stakeholders, rather than just a single cloud provider, participate in implementing and operating the cloud, thus creating an ecosystem that will bring the innovation of a broader community to bear on a much healthier and more efficient cloud marketplace

Next Generation Cloud Computing: New Trends and Research Directions

The landscape of cloud computing has significantly changed over the last decade. Not only have more providers and service offerings crowded the space, but also cloud infrastructure that was traditionally limited to single provider data centers is now evolving. In this paper, we firstly discuss the changing cloud infrastructure and consider the use of infrastructure from multiple providers and the benefit of decentralising computing away from data centers. These trends have resulted in the need for a variety of new computing architectures that will be offered by future cloud infrastructure. These architectures are anticipated to impact areas, such as connecting people and devices, data-intensive computing, the service space and self-learning systems. Finally, we lay out a roadmap of challenges that will need to be addressed for realising the potential of next generation cloud systems.Comment: Accepted to Future Generation Computer Systems, 07 September 201