Concepts about real-time marketing and use cases:
- http://en.wikipedia.org/wiki/Real-time_marketing
- http://blog.hubspot.com/blog/tabid/6307/bid/33696/7-Inspiring-Examples-of-Real-Time-Marketing-in-Action.aspx
- http://www.adweek.com/news-gallery/8-types-real-time-marketing-and-brands-got-it-right-152261#intro
- http://contentmarketinginstitute.com/2013/11/social-media-content-real-time-marketing/
- http://marketingland.com/real-time-marketing-the-use-cases-65509
- http://www.shoutlet.com/blog/2013/08/tweeting-in-real-time-six-steps-to-marketing-in-the-moment/
● Netty (http://netty.io/) a framework using reactive programming pattern for scaling HTTP system easier, by JBoss http://www.jboss.org
● Apache Kafka (http://kafka.apache.org/) a publish-subscribe messaging rethought as a distributed commit log, open sourced by Linkedin
● Storm (http://storm-project.net/) the framework for distributed realtime computation system, by Twitter
● Akka http://akka.io/ (Actor Model), a toolkit and runtime for building highly concurrent, distributed, and fault tolerant event-driven applications on the JVM.
● Redis (http://redis.io/) a advanced key-value in-memory NoSQL database, all fast statistical computations in here.
● OrientDB, an Open Source NoSQL DBMS with the features of both Document and Graph DBMSs for KPI Report Data Management http://pettergraff.blogspot.it/2014/01/getting-started-with-orientdb.html
● Groovy http://groovy.codehaus.org/ and Grails http://grails.org/ for scripting layer on JVM, ad-hoc query on Redis, and the front-end
● Hadoop ecosystem http://hadoop.apache.org/ : HDFS, Hive, HBase for batch processing
● RxJava https://github.com/Netflix/RxJava a library for composing asynchronous and event-based programs
● Hystrix https://github.com/Netflix/Hystrix : for Latency and Fault Tolerance for Distributed Systems
● NVD3 Reusable D3 Chart http://nvd3.org
- http://www.cs.iastate.edu/~patterbj/cs/Report_CS561.pdf => ideas for sample
- http://java.dzone.com/articles/flipping-coin-bayesian => write a small game
- http://www.cs.waikato.ac.nz/~eibe/pubs/Twitter-crc.pdf = > paper about how mining on stream data