NoSQL databases: Consistency of data

NoSQL databases: Consistency of data
Read consistency

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

• User consistency for the same user, access to the data during the cluster is 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 occur first, and then the process of automatic merging of sequential detection 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

     "Partition" appears in a single-server cluster, is not available

• Pa/pc

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

Relaxing "persistence" 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

Reference

The essence of NoSQL

Posted by: Big CC | 30jun,2014
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NoSQL databases: Consistency of data