We are looking into the solution that facilitate massively parallel data processing. Our processing graphs are often rather complex, so well developed operator framework like one Pervasive DataRush provides comes handy. Does anyone know any alternative solutions to one 开发者_如何学Cfrom Pervasive? DataRush is Java but I would like to consider all platforms and languages for which such solutions are available.
Not sure if you'd get usefulness out of something like hadoop/map-reduce. That's what they seem to compare themselves on their marketing collateral. Of course, they also claim that they're a better/different solution.
Pervasive DataRush exploits fine-grain parallelism on multicore servers and clusters. With the release of V5.0 on 2 Feb 2011, Pervasive DataRush now supports all JVM languages, including Java, JRuby, Python and Scala. It also supports integration with Hadoop/MapReduce. It is complementary to Hadoop.
Look at https://github.com/rfqu/df4j - simple but powerful dataflow library. Has Actors and other dataflow constructs. It lacks persistence yet, though, but has interface with NIO2 asyncronous channels
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