How to solve the inconsistency between redis cache and database double write

To solve the double-write inconsistency problem between the Redis cache and the database, the following methods can be used: Use queues: Put the data update request into the queue, making sure to write to the database first and then update the cache. Use optimistic locking: Check whether the data has been modified when updating. If it has been modified, cancel the update and notify to try again. Use event mechanism: When the database is updated, an event is triggered to notify the application to update the cache, and the application needs to listen to the database update event. Use pessimistic locking: Lock related records before writing to the database to prevent other processes from updating the same record at the same time. Use eventual consistency: Allow the cache and database to be temporarily inconsistent and rely on the application's eventual consistency mechanism to ensure eventual consistency.

How to solve the double-write inconsistency between Redis cache and database

Get straight to the point:
Common methods to solve the problem of double-write inconsistency between Redis cache and database include:

1. Use queues:
Put data update requests into the queue, and then use a dedicated process in sequence deal with. This ensures that the data is written to the database first and then the cache is updated.

2. Use optimistic locking:
Before writing to the database, check whether the data in the database has been modified. If it has been modified, cancel the update request and notify the application to try again.

3. Use event mechanism:
When the data in the database is updated, an event is triggered to notify the application to update the cache. This requires the application to implement a mechanism to listen for database update events.

4. Use pessimistic locking:
Lock related records in the database before writing to the database. This prevents other processes from updating the same record at the same time, causing inconsistencies.

5. Use eventual consistency:
Allows transient inconsistencies between the cache and the database, and relies on the application's eventual consistency mechanism to ensure eventual consistency.

Detailed explanation:

Use the queue:

• Put the update request into the queue with FIFO ( First in, first out) method.
• Write data to the database first, and then update the cache.
• If processing fails, you can retry or put the request back into the queue.

Use optimistic locking:

• Get the version number (or timestamp) of the data in the database before writing to the database.
• Check the version number when writing. If the version number has changed, roll back the transaction.
• The application needs to modify the code to adapt to the optimistic locking mechanism.

Use event mechanism:

• Implement the mechanism for subscribing to database update events.
• When data in the database is updated, the application will receive event notifications.
• After the application receives the notification, it updates the data in the cache.

Use pessimistic locking:

• Before writing to the database, lock related records to prevent other processes from accessing at the same time.
• Release the lock after writing.
• Database systems usually provide pessimistic locking mechanisms.

Use eventual consistency:

• Allow transient inconsistencies between the cache and the database.
• The application ultimately guarantees consistency through retries or other mechanisms.
• Usually suitable for non-critical data or situations where inconsistencies are tolerated.

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