Post on 12-Jul-2015
Part I
People Love Monkeys
Lowly Code Monkey
More Experienced Code Monkey
Mighty Code Ape
Mostly Human Software Architect
@DavidOstrovskySenior Solutions Architect @ Couchbase
Co-author of:“Pro Couchbase Server” – Apress Media 2014
“Essentials of Developing Windows Store Apps Using C#”
“Advanced Windows Store App Development Using C#”
Big data and NoSQL nerd
CodeHardBlog.azurewebsites.net
Part II
Doing Something Useful
What is this all about?
Couchbase + ElasticSearch + Kibana = Awesome
Why use Couchbase Server?
Document database
Scales easily
Built for performance
High throughput
Low latency
Cross-cluster replication
Why use ElasticSearch?
Fast full-text searches
Supports over a hundred languages
Geo-querying, scoring, faceting
Easy to deploy, use and scale
Huge number of plug-ins
High buzzword count
Why these two in particular?
Both use JSON documents
Complimenting strengths:
ElasticSearch for flexible search, geolocation, analytics tools, and more
Couchbase for efficient data storage and retrieval, extremely fast response times
Couchbase uses XDCR to push data to ElasticSearch
Lower latency than polling, e.g. with River
Demo
Demo time!
Common use cases
Ad-hoc querying an existing Couchbase database
Geospatial searches on data
Real-time analytics of Couchbase data
Demo
More demo time!
Kibana is a dashboard for real-time visualization of streaming data
Talks directly to ElasticSearch
Drag-and-drop dashboard construction
No coding required
Why use Kibana?
Putting it all together
A typical Couchbase-ElasticSearch deployment uses a 2:1 or 3:1 ratio of nodes
ElasticSearch only stores indexed data
Source data stored in Couchbase
All CRUD operations go to Couchbase
CouchbaseElasticSearch KibanaServer ClientCouchbase
Couchbase
Demo
So many demos!
Summary
Connecting Couchbase to ElasticSearch and Kibana is awesome!
Lets developers and analysts focus on what each does best
Provides a resilient, scalable data storage and BI solution
Fast and inexpensive
Questions