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This research represents a unique contribution to the field of Software Engineering for Big Data in the form of an investigation of the big data architectures of three well-known real-world companies: Facebook, Twitter and Netflix. The purpose of this investigation is to gather significant non-functional requirements for real-world big data systems, with an aim to addressing these requirements in the design of our own unique architecture for big data processing in the cloud: MC-BDP (Multi-Cloud Big Data Processing). MC-BDP represents an evolution of the PaaS-BDP architectural pattern, previously developed by the authors. However, its presentation is not within the scope of this paper. The scope of this comparative study is limited to the examination of academic papers, technical blogs, presentations, source code and documentation officially published by the companies under investigation. Ten non-functional requirements are identified and discussed in the context of these companies' architectures: batch data, stream data, late and out-of-order data, processing guarantees, integration and extensibility, distribution and scalability, cloud support and elasticity, fault-tolerance, flow control, and flexibility and technology agnosticism. They are followed by the conclusion and considerations for future work.

Non-functional Requirements for Real World Big Data Systems - An Investigation of Big Data Architectures at Facebook, Twitter and Netflix