Models that describe how computers and their data are organised rather than how a single program runs. The von Neumann architecture keeps instructions and data in one memory, the client-server model splits work between a provider and its requesters, the relational model arranges data in tables governed by logic, MapReduce processes large data sets across a cluster, and eventual consistency describes how replicas of data settle on one value over time.
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System Architecture and Data Models
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Wikipedia: Relational Model
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The relational model (RM) is an approach to managing data using a structure and language consistent with first-order predicate logic, first described in 1969 by English computer scientist Edgar F. Codd, where all data are represented in terms of tuples, grouped into relations.
View the Source Wikipedia: Von Neumann architecture
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The von Neumann architecture-also known as the von Neumann model or Princeton architecture-is a computer architecture based on the First Draft of a Report on the EDVAC, written by John von Neumann in 1945, describing designs by John Mauchly and J. Presper Eckert at the University of Pennsylvania's Moore School of Electrical Engineering.
View the Source Wikipedia: Client-server model
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The client-server model is a form of messaging pattern in a distributed application structure that partitions tasks or workloads between the providers of a resource or service, called servers, and service requesters, called clients.
View the Source Wikipedia: MapReduce
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MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster.
View the Source Eventual consistency - Wikipedia
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Eventual consistency is a consistency model used in distributed computing to achieve high availability.
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