Neha Narkhede: Large-Scale Stream Processing with Apache Kafka by Ralph Winzinger Posted on Jun 19, 2016
Comparison of Event Sourcing with Stream Processing by Jan Stenberg Posted on May 25, 2016
Azure Stream Analytics Publishing to Power BI Reaches General Availability by Kent Weare Posted on May 11, 2016
Apache Storm Reaches 1.0, Brings Improved Performance, Many New Features by Sergio De Simone Posted on Apr 14, 2016
Moving from Transactions to Streams to Gain Consistency by Jan Stenberg Posted on Mar 13, 2016
Netflix Details Evolution of Keystone Data Pipeline by Dylan Raithel Posted on Mar 04, 2016
Architecting Scalable, Dynamic Systems when Eventual Consistency Won’t Work by Michael Stiefel Posted on Jan 20, 2016
Lessons Learned Building Distributed Systems at Bitly by Sergio De Simone Posted on Jul 23, 2014
Big Data Processing with Apache Spark - Part 3: Spark Streaming by Srini Penchikala Posted on Jan 07, 2016 3
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 8
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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