In most modern software systems, data is the key. For more traditional architectures, the role of persisting and providing access to your system's data tends to fall to a relational database. Typically this is a monolithic beast, perhaps with a degree of replication, although this tends to be more for resilience rather than performance.
For example, here is what a traditional architecture might look like (which hopefully looks rather familiar).
This presents us with an issue in terms of application scalability, in that it is relatively easy to scale our application layer by throwing more hardware at it to increase the processing capacity. But the monolithic constraints of our data layer would only allow us to do this so far before diminishing returns or resource saturation stunted further performance increases; so what can we do to address this?
In the past and in legacy architectures, the only solution would be to increase the performance capability of our database infrastructure, potentially by buying a bigger, faster server or by further tweaking and fettling the utilization of currently available resources. Both options are dramatic, either in terms of financial cost and/or manpower; so what else could we do?
