NoSQL databases: Consistency of data

NoSQL database: Consistent read consistency for data

• Strong consistency
  Access to any node in the cluster at any time, resulting in consistent data results;

• User consistency
  The same user, access to the cluster during the data consistent;
  Resolve user consistency: Use sticky sessions to bind sessions to specific nodes for processing;
  This reduces the performance of the load balancer;

• Final consistency
  The data synchronization between the nodes in the cluster is inconsistent with the temporary data, but after the data synchronization is complete, the final consistency is achieved.

Update consistency

• Pessimistic Way

  Using write locks to significantly reduce system responsiveness can lead to deadlocks

• Optimistic Way

  Let the conflict happen first, and then the process of automatic merging is very “ domain-specific ” problem

Easing consistency constraints

• Cap theorem
  Consistency (consistency), availability (availability), and partition tolerance (Partition tolerance), 3 properties can only meet 2 at a time;

Explanation of partition tolerance: clusters are still available if the cluster is divided into multiple communications failures

• CA system

  A partition appears in a single-server cluster and is not available

• Pa/pc

  When a cluster is partitioned, a tradeoff between consistency and availability is typically sacrificed partial consistency (eg: using eventual consistency) to ensure availability

Easing persistent constraints

More stringent durability means more performance loss;

• Sacrificing persistence for better performance

• Replication Persistence failure

  Primary node failure, synchronization to data loss from node recovery, data conflict resolution updated during failure solution: Specify the persistence required for a single request

Attached Mind Map

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Reference

The essence of NoSQL

Posted by: Big CC | 02jul,2014
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