In-line caching scenarios

In-line caching uses eXtreme Scale as the primary means for interacting with the data. When eXtreme Scale is used as an in-line cache, the application interacts with the backend using a Loader plug-in.

The in-line caching option simplifies data access because it allows applications to access the eXtreme Scale APIs directly. WebSphere® eXtreme Scale supports several in-line caching scenarios, as follows.
  • Read-through
  • Write-through
  • Write-behind

Read-through caching scenario

A read-through cache is a sparse cache that lazily loads data entries by key as they are requested. This is done without requiring the caller to know how the entries are populated. If the data cannot be found in the eXtreme Scale cache, eXtreme Scale will retrieve the missing data from the Loader plug-in, which loads the data from the back-end database and inserts the data into the cache. Subsequent requests for the same data key will be found in the cache until it is removed, invalidated or evicted.
Figure 1. Read-through caching
read-through caching with a loader

Write-through caching scenario

In a write-through cache, every write to the cache synchronously writes to the database using the Loader. This method provides consistency with the back end, but decreases write performance since the database operation is synchronous. Since the cache and database are both updated, subsequent reads for the same data will be found in the cache, avoiding the database call. A write-through cache is often used in conjunction with a read-through cache.
Figure 2. Write-through caching
write-through caching with a loader

Write-behind caching scenario

Database synchronization can be improved by writing changes asynchronously. This is known as a write-behind or write-back cache. Changes that would normally be written synchronously to the loader are instead buffered in eXtreme Scale and written to the database using a background thread. Write performance is significantly improved because the database operation is removed from the client transaction and the database writes can be compressed. See Write-behind caching for more information.
Figure 3. Write-behind caching
write-behind caching with a loader

See Write-behind caching for further information.

Parent topic: Side cache and in-line cache