To simplify database schema design.

To reduce the frequency of accessing the database disk.

To improve write throughput of the database.

To avoid using load balancers.

It eliminates the need for a database.

It allows the caching layer to be scaled independently of the application servers.

It enables better enforcement of database constraints.

It reduces the number of application servers needed.

It ensures consistent cache invalidation.

It determines which cache server stores specific data.

It manages the redundancy of cache servers.

It calculates the expiration time for cached data.

Independent caching fleet.

Integrated caching within application servers.

Hybrid caching model.

Disk-based caching system.

Difficulty in caching data for infrequently accessed keys.

High traffic to specific cached data causing uneven load distribution.

Inability to cache frequently updated information.

Issues with redundancy in cached data.

Cache data not invalidating properly.

High initial traffic hitting the database until the cache is warmed up.

Inability to scale the cache horizontally.

Expired cache entries causing stale data.

To ensure the database schema remains consistent.

To balance between data freshness and cache effectiveness.

To allow caching of frequently updated data.

To reduce the need for redundancy in the cache.

Applications with frequent write operations.

Applications with a high read-to-write ratio.

Applications requiring real-time data consistency.

Applications with low user traffic.

Using a write-through caching strategy.

Preloading the cache with historical data or simulated traffic before deployment.

Shortening the cache expiration time.

Disabling caching temporarily.