Archive
June 2014

At GridGain, having worked on a distributed caching (data grid) product for many years, we constantly benchmark with various Garbage Collectors to find the optimal configuration for larger heap sizes. From conducting numerous tests, we have concluded that unless you are utilizing some off-heap technology (e.g. GridGain OffHeap), no Garbage Collector provided with JDK will render any kind of…
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If you prefer a video demo with coding examples, visit the original blog post at gridgain.blogspot.com. Distributed In-Memory Caching generally allows you to replicate or partition your data in memory across your cluster. Memory provides a much faster access to the data, and by utilizing multiple cluster nodes the performance and scalability of the application increases significantly. Majority of…
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After explaining the difference between caching and an in-memory data grid at a conference a few months ago, I realized that many people want to better understand the difference between two major categories in in-memory computing: In-Memory Database and In-Memory Data Grid. In this post, I'll share the succinct version of my thinking on this topic - thanks to a recent analyst call that helped to…
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