This fall, Wallaroo Labs will be releasing a large new feature set to our distributed data stream processing framework, Wallaroo.

In this article, authors discuss reference architecture of stream processor technologies and key features required by most streaming applications. 2

In this article, author discusses the stream processing with KSQL, the streaming SQL engine for Apache Kafka. Topics covered include challenges of stateful stream processing & how KSQL addresses them. 1

At QCon NY, Shriya Arora presented “Personalising Netflix with Streaming Datasets” and discussed a migration of a data processing job from batch-style ETL to stream processing using Apache Flink.

At QCon SF 2016, Frances Perry and Tyler Akidau presented “Fundamentals of Stream Processing with Apache Beam”, and discussed Google's Dataflow model and associated implementation of Apache Beam.

At QCon San Francisco 2016, Neha Narkhede presented “ETL is Dead; Long Live Streams”, and discussed the changing landscape of enterprise data processing. 5

Extracting useful information from inaccurate data stream, such as human trajectories, is a key issue in IoT applications. This problem can be successfully tackled with Kalman filters.

The 10th annual QCon San Francisco was the biggest yet, bringing together over 1500 team leads, architects, project managers, and engineering directors.

Internet of Things (IoT) is an emerging technology. One of the areas of IoT is the connected vehicles. In this article, we'll use Spark and Kafka to analyse and process IoT connected vehicle's data. 16

InfoQ interviews Chris Fregly, organizer for the 4000+ member Advanced Spark and TensorFlow Meetup about the PANCAKE STACK workshop, Spark and building data pipelines for a machine learning pipeline