An anonymous reader writes: In computing terms, a cache is a collection of temporary data that will be required to be accessed in the future, and can be retrieved extremely quickly. The data stored within a cache may be a simple reproduction of information held elsewhere or it may have been the results of a previous computation. Where data stored in the cache is requested, this is known as a cache hit. The advantage of a cache hit is that the request will be served considerably faster. The flipside, a cache miss, occurs when information has to be recalculated or retrieved from its original location, consuming more system resources and slower access. If 20% of data is accessed 80% of the time, and a system can be utilised which reduces the cost and time of obtaining that 20%, system performance will dramatically improve. Fine tuning a system to improve the cache hit rate speeds up overall system performance.
Caches are employed in a variety of different ways. For example, we see caches being used to store items in memory, to disk, and to a database. Caches are also frequently used to service DNS requests, as well as distributed caching where caches are used to to spread across different networked hosts.
To provide an insight into the open source software that is available, we have compiled a list of 5 of our favorite caching systems. Hopefully, there will be something of interest here for anyone who deploys applications that require predictable, low-latency, random access to data with high sustained throughput.
