Hi Leon, One thing to note is that we addressed some performance issues after benchmark is being done. I don't have environments for benchmark for the same, but worth to give it a try with recent release (1.0.1).
Thanks, Jungtaek Lim (HeartSaVioR) 2016년 6월 1일 (수) 오후 6:43, <[email protected]>님이 작성: > Hi Aaron, > > thank you very much for the link. I found it quite insightful. It is one > of the few benchmarks i have encountered where Storm comes out on top in > terms of latency, although the at-most once trade-off is quite harsh. > > Regards > Leon > > 31. May 2016 15:37 by [email protected]: > > > Hi Leon, > > This isn’t an advocacy piece per se, but this analysis by several member > of the Storm community may be helpful. For a particular use case you can > compare performance and then assess whether the features, > user-friendliness, or API of a particular framework is worth switching to. > > > https://yahooeng.tumblr.com/post/135321837876/benchmarking-streaming-computation-engines-at > > From: "[email protected]" <[email protected]> > Reply-To: "[email protected]" <[email protected]> > Date: Monday, May 30, 2016 at 3:28 AM > To: "[email protected]" <[email protected]> > Subject: Storm unique strengths > > Hi Storm team, > > there are a lot of online comparisons between Storm and other Data Stream > Management Systems, yet few of them originate from Storm > committers/advocats. > I am trying to identify the aspects that Storm possesses, which make it > stand out among its direct competitors. Currently there is significant > competition from Apache Flink, although less so from Spark due to its > seconds latency restriction. > > From my experience Storm offers a unique support for DSLs, as well as a > very flexible concept of Spouts and Bolts. Other aspects however seem to > have been improved upon by Flink in greater part. > > Would you be able to direct me to resources that argue more towards > Storm's case? > > Thanks in advance. > > Leon > >
