Peter Cnudde on How Yahoo Uses Hadoop, Deep Learning and Big Data Platform by Srini Penchikala Posted on Oct 13, 2016
Data Lake-as-a-Service: Big Data Processing and Analytics in the Cloud by Srini Penchikala Posted on Dec 10, 2015
Big Data as a Service, an Interview with Google's William Vambenepe by Chris Swan Posted on Jul 06, 2015
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 8
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
Google Cloud Machine Learning and Tensor Flow Alpha Release by Dylan Raithel Posted on Apr 18, 2016
MemSQL 4 Database Supports Community Edition, Geospatial Intelligence and Spark Integration by Srini Penchikala Posted on May 30, 2015
Glenn Tamkin on Applying Apache Hadoop to NASA's Big Climate Data by Srini Penchikala Posted on May 06, 2015
Hortonworks, IBM and Pivotal to Support Open Data Platform in Their Big Data Solutions by Srini Penchikala Posted on Apr 24, 2015
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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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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