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Applied in cases like NoSQL
- In the CAP theorem, in a state where A and P are maintained
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The opposite of ACID Properties in Relational Databases? (Genius naming)
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Even if a part of the system goes down, the system continues to function
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The system’s data is constantly changing
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As long as consistency is eventually guaranteed, it’s okay (loose consistency)
- In cases where strong consistency is required (ACID Properties, etc.), = reads following writes are always updated immediately
- With Eventual Consistency, this is not the case
- It’s okay to have a lag between a write and the update of a read value
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”Quorum”: A technology used in NoSQL and other distributed systems to maintain processing consistency
- It aims to avoid Write-Write conflicts (where one is overwritten) and Read-Write conflicts (where incorrect data is read)
- By simultaneously reading/writing to multiple replicas, safety is more likely to be ensured
- Specifically,
- To avoid Write-Write conflicts: w > n/2
- To avoid Read-Write conflicts: r > n-2
- (where n is the total number of replicas, w is the number of replicas writing simultaneously, and r is the number of replicas reading simultaneously)
- There are conditions like these.
- Specifically,