Maybe also take into account the new heron https://blog.twitter.com/2016/open-sourcing-twitter-heron
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -. F1 Outsourcing Development Sp. z o.o. Poland t: +48 (0)124466845 f: +48 (0)124466843 e: [email protected] -----Original Message----- From: [email protected] [mailto:[email protected]] Sent: woensdag 1 juni 2016 11:44 To: User Cc: [email protected] Subject: Re: Storm unique strengths 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-streamin g-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
