How does redis cache maintain a consistent state with the database

Methods to ensure that the Redis cache is consistent with the database include: 1. Passive consistency periodic synchronization; 2. Incremental synchronization; 3. Active consistency (subscribing to database events); 4. Use distributed transactions. The method chosen depends on data lag tolerance, performance requirements, and database support.

Consistency between Redis cache and database

Question:How to ensure that Redis cache is consistent with Is the database in a consistent state?

Answer: Common methods to ensure that the Redis cache is in a consistent state with the database include:

Passive consistency

• Periodic synchronization: Synchronize database data to the Redis cache regularly, such as once every hour or every day. This method is simple, but may have data lag.
• Incremental synchronization: When database data changes, incrementally synchronize the changes to the Redis cache. This can reduce data lag, but requires a more complex implementation.

Active consistency

• Subscribe to database events: By subscribing to database events (such as INSERT, UPDATE, DELETE), When database data changes, the Redis cache can be updated immediately. This ensures minimal data lag, but requires the database to support event notifications.
• Use distributed transactions: Wrap database read and write operations and Redis cache update operations in distributed transactions. If the transaction commits successfully, both the database and the Redis cache will be updated. This ensures strict consistency but may impact performance.

Choose a method

Which method you choose depends on the needs and limitations of your application:

• Data lag Tolerance: If the application can tolerate a certain amount of data lag, the passive synchronization method may be sufficient.
• Performance requirements: Active consistency methods generally have better performance than passive consistency methods, but may be more complex.
• Database support: Confirm whether the database supports event notifications to determine whether it is feasible to subscribe to database events.

Other considerations

• Expiration policy: Set an expiration time for data in the cache to limit data lag.
• Cache invalidation: When the database data changes, the relevant data in the cache is immediately invalidated to ensure consistency.
• Performance Optimization: Use an in-memory database or other caching mechanism to enhance cache performance to reduce data lag.

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