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One reason for the success of in-memory (transactional) data grids lies on their ability to t elasticity requirements imposed by the cloud oriented pay-as-you-go cost model. In fact, by relying on in-memory data maintenance, these platforms can be dynamically resized by simply setting up (or shutting down) instances of so called data cache servers. However, defining the well suited amount of cache servers to be deployed, and the degree of in-memory replication of slices of data, in order to optimize reliability/availability and performance tradeoffs, is far from being a trivial task.
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