How redis solves data consistency
Redis provides two consistency models to maintain replica data consistency: strong consistency (SYNC) ensures that write operations are only completed after being copied to all slave nodes; eventual consistency (ASYNC) The write operation on the master node is considered completed, sacrificing consistency for performance. In addition, optimistic locking and atomic operation mechanisms can further enhance client consistency. Choosing a consistency model should be based on the trade-off between the application's consistency requirements and performance sensitivity.
How does Redis solve data consistency
What is consistency?
In a distributed system, consistency ensures that the data on all replicas is always consistent. This means that all reads return the same value and all writes are applied to all replicas in the same order.
Consistency model of Redis
Redis is a database with a single-master and multiple-slave architecture, which means that it has one master node and multiple slave nodes. The master node is responsible for receiving write operations and replicating them to the slave nodes.
Redis provides the following consistency models:
1. Strong consistency (SYNC)
- Available in versions prior to Redis 3.0.
- A write operation is considered committed only after it has been successfully replicated to all slave nodes.
- Provides the strongest guarantee, but will also cause performance degradation.
2. Eventual consistency (ASYNC)
- Used by default in Redis 3.0 and later.
- A write operation is considered committed on the master node, even if it has not been replicated to the slave node.
- Higher performance, but may cause temporary inconsistencies.
Client Consistency
In addition to using the SYNC or ASYNC consistency model, Redis also provides some mechanisms to ensure client consistency:
- Optimistic Locking: Allows the client to check the version of the data and verify that the version is still the latest before modifying the data.
- Atomic Operations: Provides a set of atomic operations to ensure that multiple commands either all execute successfully or all fail.
Application scenarios
Selecting an appropriate consistency model depends on the needs of the specific application:
- High requirements for consistency and performance Non-sensitive applications should use the SYNC consistency model.
- Applications that have high performance requirements and can tolerate temporary inconsistencies should use the ASYNC consistency model.
By using the above mechanisms, applications can control data consistency in Redis to meet their specific requirements.
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