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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Designing a Highly Available, Fault Tolerant, Hadoop Cluster with Data Isolation by Monica Beckwith Posted on Dec 16, 2014
Interview with Alex Holmes, author of “Hadoop in Practice. Second Edition” by Boris Lublinsky Posted on Nov 20, 2014
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 5
Nikita Ivanov on GridGain’s In-Memory Accelerator for Hadoop by Srini Penchikala Posted on Sep 08, 2014
Rich Reimer on SQL-on-Hadoop Databases and Splice Machine by Srini Penchikala Posted on Jun 19, 2014
Lambda Architecture: Design Simpler, Resilient, Maintainable and Scalable Big Data Solutions by Daniel Jebaraj Posted on Mar 12, 2014 7
Big Data Analytics for Security by Alvaro A. Cárdenas, Pratyusa K. Manadhata, Sreeranga P. Rajan Posted on Feb 11, 2014
Splice Machine Version 1.0 Supports Integration with Hadoop and Analytic Window Functions by Srini Penchikala Posted on Dec 18, 2014
LinkedIn Open Sources Cubert With an Eye To Big Data Analytics by Alex Giamas Posted on Dec 17, 2014
Gobblin, LinkedIn's Unified Data Ingestion Platform by Mikio Braun Posted on Dec 15, 2014
Hortonworks Data Platform Makes an Enterprise Push by Rags Srinivas Posted on Nov 14, 2014
Microsoft Expands Azure Machine Learning and Real Time Analytics Offering by Alex Giamas Posted on Oct 31, 2014
Hadoop ecosystem capabilities: What to add next?
The last 5 years the Hadoop ecosystem has expanded rapidly to satisfy for various production needs. Most recently a number of real-time workloads and tools have been brought to this new generation data processing and management platform.
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Τrends of different Big Data Solutions
Various Hadoop-based solutions for a new generation of data management have disrupted the market of traditional data processing and management systems in recent years. There is no longer a question on whether enterprises need a big data strategy - it has become a fact! But the questions remains - when and how to migrate?
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