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Uploaded by VigilantCopernicium
Chandil Polytechnic School
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This document provides a summary of data-centric consistency models. It explains how these models maintain data integrity in distributed systems and the different types of consistency, such as strict, sequential, causal, and FIFO. It also compares this with client-centric models, highlighting the trade-offs between speed and consistency.
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Text Summary https://play.google.com/store/apps/details?id=com.aya.textsummarizer - Data-centric consistency models focus on maintaining data integrity in distributed systems, defining how updates are synchronized across nodes to ensure all clients see a consistent view. - Types of data-centric co...
Text Summary https://play.google.com/store/apps/details?id=com.aya.textsummarizer - Data-centric consistency models focus on maintaining data integrity in distributed systems, defining how updates are synchronized across nodes to ensure all clients see a consistent view. - Types of data-centric consistency include strict, sequential, causal, and FIFO consistency, each offering different guarantees and trade-offs based on application needs and performance considerations. - Client-centric models prioritize individual client views, allowing for faster response times and occasional inconsistencies, while data-centric models emphasize global consistency and stronger data guarantees, potentially at the cost of performance.
