Real-time Data Analytics at Pinterest using MemSQL and Spark Streaming by Srini Penchikala Posted on Mar 29, 2015
Apache Spark 1.3 Released, Data Frames, Spark SQL, and MLlib Improvements by Mikio Braun Posted on Mar 16, 2015
Google Open Sources MapReduce Framework for C to Run Native Code in Hadoop by Srini Penchikala Posted on Feb 25, 2015
MongoDB 3.0 - WiredTiger Storage Engine and Updated MMS by Alex Giamas Posted on Feb 20, 2015
Project Pachyderm Aims to Build a "Modern" Hadoop on Docker by Matt Kapilevich Posted on Feb 17, 2015 3
Apache Hive 1.0 Released, HiveServer2 Becomes Main Engine, Stable API Defined by Mikio Braun Posted on Feb 11, 2015
Highly Distributed Computations Without Synchronization by Christopher Meiklejohn Posted on Feb 17, 2015 1
Big Data Processing with Apache Spark – Part 1: Introduction by Srini Penchikala Posted on Jan 30, 2015 2
Apache Ignite GridGain Incubator Project - Q&A Interview with Nikita Ivanov by Srini Penchikala Posted on Dec 03, 2014
Interview with Alex Holmes, author of “Hadoop in Practice. Second Edition” by Boris Lublinsky Posted on Nov 20, 2014
Analytics Across the Enterprise: How IBM Realizes Business Value from Big Data and Analytics by Alex Giamas Posted on Oct 27, 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 6
Emerging Trends in Big Data Technologies
Big Data technologies have been getting lot of attention over the last few years. There are several trends and innovations happening in this space. InfoQ would like to learn what new trends in Big Data you are currently using or planning on using in the future.
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.
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?