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Industry Survey Shows: Organizations Turn to Stream Processing for their Big Data Needs

Published on December 16, 2013 by in GigaSpaces

In a stream processing model, data is processed as it arrives to the Big Data system. With a batch processing model, only once the data is stored does the system run a variety of batch analytics – typically through a map/reduce style of processing. Facebook and Twitter are good examples of stream processing models in

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XAP on Cloudify Part 2 : Multi-site Replication

Introduction Since version 8, XAP has had the capability to replicate data between spaces across multiple sites. The capability is well described in the product wiki. Although many scenarios are supported, the canonical use case is that of replication between multiple sites in a WAN context, for either disaster recovery or geographical load balancing. As

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Industry Survey Shows: Organizations Turn to Stream Processing for their Big Data Needs

In a stream processing model, data is processed as it arrives to the Big Data system. With a batch processing model, only once the data is stored does the system run a variety of batch analytics – typically through a…

 
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