Scaling with Couchbase, Kafka and Apache Spark

Couchbase at Symantec

Relationships between data matter even in this modern world of flexible type. Gaurav from Symantec will give an overview of how Symantec have deployed systems such as Couchbase and ElasticSearch for two different needs. First, a time series use case which leverages the common, heterogenous JSON data structure between Couchbase and ElasticSearch allowing each to meet Symantec’s needs. The second deals with entities and the various relationships between them. How should one model these relationships in a world with a flexible schema?

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

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:

Gaurav Chandna (http://twitter.com/xyxxy), Engineering Manager at Symantec will lead a discussion on scaling out, up, and down with Couchbase Server.

Matt Ingenthron (https://twitter.com/ingenthr)Couchbase Sr. Director Developer Experience and SDK Engineering will then talk about Couchbase in high scale, big data deployments.