Fast Data: Parallel Processing on the Grid.
You may think of in-memory datagrids as a big cache, a key value store accessed using put and get. However to really reap the power and scale of modern data grids you need to move beyond cache semantics and turn your architecture on its head. Moving the processing to the data rather than pulling the data across the grid massively increases parallelism and reduces network latency, leading to huge increases in throughput. In this session, we will explore why traditional cache semantics sometimes struggles to scale and how through using parallel processing and event processing on the grid we can rearchitect our systems for massive scalability and utilise all our grid cores for parallel processing.