Real-Time Stream Processing as Game Changer in a Big Data World with Hadoop and Data Warehouse by Kai Wähner Posted on Sep 10, 2014 7
Lessons Learned Building Distributed Systems at Bitly by Sergio De Simone Posted on Jul 23, 2014
Microsoft Tackles Internet-of-Things With New Data Stream Processing Service by Richard Seroter Posted on Jul 22, 2014 1
New York Times Lab Introduces Visual Stream Processing Tool by Michael Hausenblas Posted on Apr 01, 2014 1
Dempsy – a New Real-time Framework for Processing BigData by Boris Lublinsky Posted on Apr 25, 2012 8
Yahoo! Releases S4, a Real Time, Distributed Stream Computing Platform by Tim Cull Posted on Nov 23, 2010 5
Event Stream Processing: Scalable Alternative to Data Warehouses? by Sadek Drobi Posted on Oct 31, 2008
WebSphere Updates: sMash, eXtreme Scale, Virtual Enterprise, Business Events by Floyd Marinescu Posted on Apr 09, 2008
Gartner on Disruptive Trends in Platform Middleware by Mark Figley Posted on Oct 18, 2007 1
Catching up with Esper: Event Stream Processing Framework by Floyd Marinescu,Thomas Bernhardt Posted on Oct 12, 2007 5
Building Complex Event Processing applications in Java with WebLogic Event Server by Gavin Terrill Posted on Aug 27, 2007
InfoQ Article: Using SEDA to Ensure Service Availability by Miko Matsumura Posted on Oct 12, 2006 5
Martin Kleppmann on Using Logs for Building Data Infrastructure, CAP, CRDTs
Jun 28, 2015
Martin Kleppmann explains how logs are used to implement systems (DBs, replication, consensus systems, etc), integrating DBs and log-based systems, the relevance of CAP and CRDTs, and much more.
Darach Ennis on CEP, Stream Processing, Messaging, OOP vs Functional Architecture
May 09, 2013
Darach Ennis explains the lessons learned from the Complex Event Processing community, reactive programming, the challenges of messaging on mobile platforms, OOP vs Functional and much more.
InfoQ eMag: Hadoop
Apache Hadoop is proving useful in deriving insights out of large amounts of data, and is seeing rapid improvements. Hadoop 2 now goes beyond Map-Reduce; it is more modular, pluggable and flexible and it fits a variety of use cases better. We explore this as well as some tools that can help utilize Hadoop better.
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