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


Details
Description:
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.
Speaker:
Matt is Senior Director of Developer Experience and SDK engineering at Couchbase with a long software development background. He has been a contributor to the memcached project, one of the maintainers of the Java spymemcached client and a core developer on Couchbase. He is currently heading up Couchbase's work in helping ramp up developers with Couchbase and getting the right bits needed for Java, .NET, Node.js, Go and Ruby developers (among others).
Lightning Talk
We shall also have David Lewis from BNY Mellon deliver a lightning talk on “Cloud Persistence Challenges and Opportunities for Financial Services”, so don't be late.

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