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Consistency Models
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Monotonic Read Consistency
A system ensures that if a transaction reads data, any successive reads will always see that data or newer data. It is used in systems that require reliable progressive reads.
Strict Consistency
Every read operation gets the most recent write operation. It is used in systems where read and write operations need to be instantly visible to all nodes.
Linearizability
A stronger condition than sequential consistency, every operation appears instantaneously at some point between its invocation and its response. Used in distributed data stores.
Eventual Consistency
If no updates are made to a distributed system, eventually all accesses will return the last updated value. Used in large-scale distributed systems like DNS and some databases.
Causal Consistency
If one operation causally influences another operation, the system must guarantee that all processes observe the first operation before the second. Used in replicated databases and collaborative software.
Sequential Consistency
The result of any execution is the same as if the operations of all processors were executed in some sequential order. It is used in shared memory systems.
Read-your-writes Consistency
Guarantees a system records the latest write operation by a user, so future read operations by the same user will return that data. Common in user-centric applications.
Monotonic Write Consistency
A system ensures that a write operation by a process will be completed before any subsequent write operations by that same process. Used in systems to maintain write order.
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