Using Read-through and Write-through in Distributed Cache

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Using Read-through and Write-through in Distributed Cache

With the explosion of extremely high transaction web apps, SOA, grid computing, and other server applications, data storage is unable to keep up. The reason is data storage cannot keep adding more servers to scale out, unlike application architectures that are extremely scalable.

In these situations, in-memory distributed cache offers an excellent solution to data storage bottlenecks. It spans multiple servers (called a cluster) to pool their memory together and keep all cache synchronized across servers, and it can keep growing this cache cluster endlessly, just like the application servers. This reduces pressure on data storage so that it is no longer a scalability bottleneck.

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