Traffic Data Monitoring Using IoT, Kafka and Spark Streaming by Amit Baghel Posted on Sep 28, 2016 1
Big Data Processing with Apache Spark - Part 5: Spark ML Data Pipelines by Srini Penchikala Posted on Sep 24, 2016
Chris Fregly on the PANCAKE STACK Workshop and Data Pipelines by Dylan Raithel Posted on Aug 29, 2016
Christine Doig on Data Science as a Team Discipline by Srini Penchikala Posted on Aug 26, 2016
Big Data Analytics with Spark Book Review and Interview by Srini Penchikala Posted on Jun 23, 2016
Big Data Processing with Apache Spark - Part 4: Spark Machine Learning by Srini Penchikala Posted on May 15, 2016
Amazon Kinesis Analytics is Like SaaS for Big Data Analysis by Elton Stoneman Posted on Sep 14, 2016
IBM Creates Artificial Neurons from Phase Change Memory for Cognitive Computing by Srini Penchikala Posted on Sep 13, 2016
Azure Premium Messaging Service Reaches General Availability by Kent Weare Posted on Jul 31, 2016
Basho Open Sources Time Series Database Riak TS 1.3 by Rags Srinivas Posted on Jul 15, 2016
Meson Workflow Orchestration and Scheduling Framework for Netflix Recommendations by Srini Penchikala Posted on Jul 10, 2016
Google BigQuery Now Allows to Query All Open-Source Projects on GitHub by Sergio De Simone Posted on Jul 08, 2016 2
Neha Narkhede: Large-Scale Stream Processing with Apache Kafka by Ralph Winzinger Posted on Jun 19, 2016
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?