Why Rfx for Big Data Application

We are in the Data-Driven Age or "data-driven society". New demands, mean some open source projects would be born  to solve new kind of problems.
More information can be found here:
http://www.technologyreview.com/review/526561/the-limits-of-social-engineering
http://socialphysics.media.mit.edu

Tapping into big data, researchers and planners are building mathematical models of personal and civic behavior. But the models may hide rather than reveal the deepest sources of social ills.

There are some good tools for developing some practical solutions:

• Most popular platform is Hadoop: http://hadoop.apache.org

Some promising projects, which complement Hadoop for more advanced features

• http://projects.spring.io/spring-xd : apply Enterprise Design Patterns for Big Data App
• http://spark.apache.org : faster, cooler, fun
• http://storm.incubator.apache.org : simple, real-time, streaming data processing

and what about Rfx ? 
simple, reactive, real-time, streaming data processing, full-stack and awesome !

• Ideas since 2007 (from Haskell and Actor model theory)
• R&D and Deployed in Production since 2013

• Open Source: Apache License, Version 2.0 
• Full Stack: backend+frontend for real-time big data framework
• Backend: Data Crawler/Importer/Exporter + Kafka + Netty + Akka + Redis
• Frontend: Groovy/Java Restful API + WebSocket + HTML5 + AngularJS + D3 + Bootstrap

• Apply Agile for Analytic and Data Science (Continuous Delivery)
• Apply & Implement Reactive Lambda Architecture
• Really fast and near-real-time processing
• Tested with 1.000.000 logs / second (1 million in 1 second)
• Simple development model for big data developer

Current git repo source: https://bitbucket.org/trieunt/rfx/wiki/Home