How to choose the solution for data consistency between MySQL and Redis: the difference between delayed double deletion and first modifying the database and then deleting the cache and applicable scenarios?

MySQL and Redis data consistency: Comparison of delayed double deletion and first modifying the library and then deleting the cache

When dealing with MySQL and Redis data consistency, "delayed double deletion" and "first library modification and then cache removal" are two common strategies, each with its advantages and disadvantages, and the applicable scenarios are different. This article will analyze the differences and application of the two in detail.

Detailed explanation of delayed double deletion

Delay double deletion is to add a delayed deletion step based on the "first modify the library and then delete the cache" to ensure final consistency. The core is to avoid the old data being rewrite to the cache during cache failure.

Specifically, if the cache fails, another request reads the database. If database modification and cache deletion are completed but new data has not been written to the cache, the old data will be written to the cache, resulting in inconsistency. Delayed double deletion by deleting the cache twice to ensure that new data is updated to the cache in a timely manner.

Detailed explanation of the library first and then delete cache

"Change the library first and then delete the cache" is more direct: modify the database first, and then delete the cache immediately. Its logic depends on the cache read mechanism: when the cache is missing, the application will read data from the database and update the cache. Therefore, deleting the cache immediately after modifying the database can ensure that new data is read next time.

Applicable scenario analysis

Applicable scenarios for delayed double deletion:

• High concurrency read and write scenarios: Under high concurrency, the probability of cache failure and data modification occurring simultaneously increases, and delayed double deletion can effectively avoid data inconsistency.
• Scenarios with extremely high data consistency requirements: businesses such as finance and orders that require extremely high data consistency requirements, delaying double deletion provides more reliable guarantees.

Applicable scenarios for modifying the library first and then deleting the cache:

• Read more and write less scenarios: The probability of cache failure and data modification occurring simultaneously is low, and directly deleting the cache can meet the consistency needs.
• Scenarios with high timeliness requirements: This solution can reflect data changes faster.

Mainstream solutions in the industry

At present, "changing the library first and then deleting the cache" is more common. Its implementation is simple and can meet consistency requirements in most scenarios. However, in scenarios where data consistency is extremely high, "delayed double deletion" is more suitable.

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