Big Data Trendz

Thanks to  Ted Malaska  and Cloudera Evaluating which streaming architectural pattern is the best match to your use case is a precondition for a successful production deployment. The Apache Hadoop ecosystem has become a preferred platform for enterprises seeking to process and understand large-scale data in real time. Technologies like Apache Kafka, Apache Flume, Apache Spark, Apache Storm, and Apache Samza are increasingly pushing the envelope on what is possible. It is often tempting to bucket large-scale streaming use cases together but in reality they tend to break down into a few different architectural patterns, with different components of the ecosystem better suited for different problems. In this post, I will outline the four major streaming patterns that we have encountered with customers running enterprise data hubs in production, and explain how to implement those patterns architecturally on Hadoop. Streaming Patterns The four basic streaming patterns (o...