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The CAP Theorem and Trade-Offs Suggested

Eric Brewer predicted, at the 2000 Symposium on Principles of Distributed Computing (PODC), that in any networked shared-data system there is a fundamental trade-off between consistency, availability, and partition tolerance. The CAP theorem states that any networked shared-data system can have at most two of three desirable properties:
• Consistency (C) equivalent to having a single up-to-date copy of the data
• High availability (A) of that data (for updates)
• Tolerance to network partitions (P)
In 2012, Brewer modified the CAP theorem, pointing out that all the CAP properties are more or less continuous and possible to optimize, weighing them against each other. This means that, in practice, it is possible to have both relative high availability and sufficient data consistency—despite the presence of network partitions.
CAP theorem poses a theoretical problem for cloud computing, where services are founded on massively distributed servers for their computer and storage.

To prepare:
• Review the Brewer article, “CAP Twelve Years Later: How the “Rules” Have Changed,” found in this week’s Learning Resources (in sources below)

Use this for each paragraph:

Post a 350- to 500-word response in APA7 format in which you include:

• Provide a critical analysis of the data storage models for a NoSQL database and their potential to satisfy each of the following combinations of C, A, and P of CAP:
• CA (consistency and availability)
• AP (availability with partition tolerance)
• CP (consistency with partition tolerance)
• Suggest specific scenarios from your professional working environment (or a working environment you are familiar with), where one data storage model should be preferred over the other for each of the cases of CA, AP, and CP.
• Explain why.