Paul King reviews the features in Groovy which make it easy to work with databases - Groovy SQL, datasets -, and working with NoSQL databases such as MongoDB and Neo4J.
Christoph Strobl focuses on integrating search solutions like Solr, Elasticsearch as well as MongoDBs full text search into an application.
Christopher Meiklejohn looks at applying two techniques together, deterministic data flow programming and conflict-free replicated data types, to create highly available and fault-tolerant systems.
Andrew Kennedy talks about the reasons for creating a Docker cloud and how Clocker was born.
Ken Kousen discusses combining various technologies: Groovy, Ratpack, MongoDB, Grails, REST.
This talk provides a broad overview of the new features introduced in the latest Spring Data release trains: recent additions in Spring Data Commons and the latest features of individual store modules
Sponsored by Basho. Sean Cribbs discusses the theory behind several rich data types introduced with Riak 2.0 and then walking through some example applications that use them in popular languages.
In this solutions track talk, sponsored by MongoDB, Matt Asay discusses the differences between some of the NoSQL and SQL databases and when Hadoop makes sense to be used with a NoSQL solution.
Trisha Gee demoes building a web application using Java, HTML5, Angular.js, Mongo.DB, Groovy and microservices in one hour.
Details on Pinterest's architeture, its systems -Pinball, Frontdoor-, and stack - MongoDB, Cassandra, Memcache, Redis, Flume, Kafka, EMR, Qubole, Redshift, Python, Java, Go, Nutcracker, Puppet, etc.
Garrett Eardley explores how Riot Games is using Riak for their stats system, discussing why they chose Riak, the data model and indexes, and strategies for working with eventually consistent data.