A recent one is "Analytics on Fast Data: Main-Memory Database Systems versus Modern Streaming Systems" ( http://db.in.tum.de/~kipf/papers/fastdata.pdf)
For the record, the paper above doesn't yet cover/realize that, nowadays, the Kafka project includes native stream processing capabilities aka the Kafka Streams API. -Michael On Thu, Mar 23, 2017 at 2:00 PM, Felix Neutatz <neut...@googlemail.com> wrote: > Hi, > > our team already created a benchmark framework for batch processing > (including MR,Yarn, Spark, Flink), maybe you like to extend it for > streaming: https://github.com/peelframework/peel > > Best regards, > Felix > > > On Mar 23, 2017 11:51, "Christophe Salperwyck" < > christophe.salperw...@gmail.com> wrote: > > Good idea! You could test Akka streams too. > > Lots of documents exist: > https://yahooeng.tumblr.com/post/135321837876/benchmarking-s > treaming-computation-engines-at > https://github.com/yahoo/streaming-benchmarks > > Cheers, > Christophe > > 2017-03-23 11:09 GMT+01:00 Giselle van Dongen <giselle.vandon...@ugent.be> > : > >> Dear users of Streaming Technologies, >> >> As a PhD student in big data analytics, I am currently in the process of >> compiling a list of benchmarks (to test multiple streaming frameworks) in >> order to create an expanded benchmarking suite. The benchmark suite is >> being >> developed as a part of my current work at Ghent University. >> >> The included frameworks at this time are, in no particular order, Spark, >> Flink, Kafka (Streams), Storm (Trident) and Drizzle. Any pointers to >> previous work or relevant benchmarks would be appreciated. >> >> Best regards, >> Giselle van Dongen >> > > >
