Well, you can only store data in Kafka, you can't put application logic in there.
Storm is good for processing data, but it is not a data store, so that is out. Redis might work, but it is only an in-memory store (seems like it does have persistence, but I don't know much about that). You could try using Kafka and Storm to write the data to something like Cassandra or Elasticsearch, and perform your analysis later on the data set as it lives in there. Philip On Aug 28, 2013, at 5:10 AM, Yavar Husain <yavarhus...@gmail.com> wrote: > I have an application where I will be getting some Time Series data which I > am feeding to Kafka and Kafka in turn is giving data to Storm for doing > some real time processing. > > Now one of my use case is that there might be certain lag in my data. For > an example: I might not get all the data for 2:00:00 PM all together. There > is a possibility that say all the data for 2:00:00 PM does not arrive at a > time and the application has to wait for all the data to arrive to perform > certain analytics. > > For example, say at 2:00:00 pm I get 990 points and another 10 points (say > I know beforehand that there would be 1000 points of data per millisecond) > arrive at 2:00:40 PM. Now I have to wait for all the data to arrive to > perform analytics. > > Where should I place my application logic: (1) In Kafka, (2) In Storm or > should I use something like Redis to get all the timestamped data and when > I get all the points for a particular time than only I give it to > Kafka/Storm. > > I am confused :) Any help would be appreciated. Sorry for any grammatical > errors as I just was thinking aloud and jotting down my question. > > Regards, > Yavar
