Couchbase 4.6 Developer Preview Released, Adds Real-Time Connectors for Apache Spark 2.0 and Kafka by Posted on Nov 28, 2016
Spark Summit EU Highlights: TensorFlow, Structured Streaming and GPU Hardware Acceleration by Posted on Nov 13, 2016
Microsoft Releases Data Science Tools for Interactive Data Exploration and Modeling by Posted on Nov 07, 2016
Microservices and Stream Processing Architecture at Zalando Using Apache Flink by Posted on Oct 31, 2016 1
Wolfram Wants to Deliver “Computation Everywhere” with New Private Cloud by Posted on Oct 26, 2016
Stream Processing and Lambda Architecture Challenges by Posted on Oct 19, 2016 4
Jay Kreps on Distributed Stream Processing with Apache Kafka and Kafka Streams by Posted on Oct 16, 2016
Reactive Summit 2016 Conference: Reactive Microservices and Staging Data Pipelines by Posted on Oct 08, 2016
Confluent Announces Kafka for the Enterprise with Multi-Datacenter Replication by Posted on Oct 05, 2016
Amazon Kinesis Analytics is Like SaaS for Big Data Analysis by Posted on Sep 14, 2016
Case Study: Selecting Big Data and Data Science Technologies at a large Financial Organisation by Posted on Nov 10, 2016
Peter Cnudde on How Yahoo Uses Hadoop, Deep Learning and Big Data Platform by Posted on Oct 13, 2016
Traffic Data Monitoring Using IoT, Kafka and Spark Streaming by Posted on Sep 28, 2016 4
Big Data Processing with Apache Spark - Part 5: Spark ML Data Pipelines by Posted on Sep 24, 2016 1
Spark GraphX in Action Book Review and Interview by Posted on Sep 12, 2016
Chris Fregly on the PANCAKE STACK Workshop and Data Pipelines by Posted on Aug 29, 2016
Christine Doig on Data Science as a Team Discipline by Posted on Aug 26, 2016
Big Data Analytics with Spark Book Review and Interview by Posted on Jun 23, 2016
Big Data Processing with Apache Spark - Part 4: Spark Machine Learning by Posted on May 15, 2016
The Role of a Data Scientist in 2016 by Posted on Mar 27, 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?