Wikibon produced an interesting material (looks like paid by Aerospike, NoSQL database recently emerged by resurrecting failed CitrusLeaf and acquihiring AlchemyDB, which product, of course, was recommended in the end) that compares NoSQL databases based on storing data in flash-based SSD vs. storing data in DRAM.
There are number of factual problems with that paper and I want to point them out…
GridGain is Java-based middleware for in-memory processing of big data in a distributed environment. It is based on high performance in-memory data platform that integrates fast In-Memory MapReduce implementation with In-Memory Data Grid technology delivering easy to use and easy to scale software. Using GridGain you can process terabytes of data, on 1000s of nodes in under a second.…
Dmitriy Setrakyan provided an excellent explanation for in-memory data grids (IMDG) in his blog In-Memory Data Grids... Explained.
I will try to provide a similar description for in-memory compute grid (IMCG). Learn more about GridGain in-memory compute grids here.
IMCG - In-Memory Compute Grid
One of the main ideas Dmitriy put forward is the importance of integration between in-memory storage…
GridGain 4.3.1 service release includes several important bug fixes and host of new optimizations. It is 100% backward compatible and it is highly recommended update for anyone running production systems on 4.x code line.
November 10th, 2012
New Features and Enhancements
Added remove operation to data loader
In-memory processing has been a pretty hot topic lately. Many companies that historically would not have considered using in-memory technology because it was cost prohibitive are now changing their core systems’ architectures to take advantage of the low-latency transaction processing that in-memory technology offers. This is a consequence of the fact that the price of RAM is dropping…