Couchbase, Kafka, Spark, Hadoop - Polyglot Persistence and the Big Data Pipeline

Title: Couchbase, Kafka, Spark, Hadoop - Polyglot Persistence and the Big Data Pipeline

Abstract: Tracking user events as they happen with a rate up to millions of operations per second can challenge anyone providing real time user interaction. It requires both huge scale and a lot of processing to support dynamic adjustment to targeting products and services. Couchbase accommodates fast access to primary app data for interactive apps at scale while providing interfaces to Apache Spark and Kafka to stream data to Hadoop for deep analytics. As the operational data store Couchbase data services are easily capable of processing tens of millions of updates a day, or more. Streaming through systems such as Apache Spark and Kafka into Hadoop, information about these key events can be turned into deeper knowledge. These variations on the Lambda architecture are already deployed at sites like PayPal, Live Person and LinkedIn

Speakers: Justin Michaels, Solution Architect at Couchbase

With over 20 years experience in deploying mission critical systems, Justin Michaels industry experience covers capacity planning, architecture and industry vertical experience. Justin brings his passion for architecting, implementing and improving Couchbase to the community as a Solution Architect. His expertise involves both conventional application platforms as well as distributed data management systems. He regularly engages with existing and new Couchbase customers in performance reviews, architecture planning and best practice guidance.