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.
Paul King presents working with databases in Groovy, covering datasets, GMongo, Neo4J, raw JDBC, Groovy-SQL, CRUD, Hibernate, caching, Spring Data technologies, etc.
Tom Coupland discusses some of the various technologies investigated, and in many cases deployed at Nokia including Gradle, Spring, MongoDB and Clojure.
Tony Tam shares tips for modeling data with MongoDB for a fast and scalable system based on his experience migrating billions of records from MySQL to MongoDB.
Kenny Gorman provides advice on designing systems using MongoDB in order to avoid some of the pitfalls lurking along the way.
Peter Bell introduces 4 NoSQL categories –Key-Value, Document, Column, Graph - and explains how one can use Spring Data to work with such data stores.
Ross Lawley introduces MongoDB, explaining why it is a good solution for cloud deployment.
Richard Kreuter and Kyle Banker on how to avoid classical RDBMS transactional systems by using compensation mechanisms, transactional messaging or transactional procedures.
Chris Richardson shows how he ported a relational database to three NoSQL data stores: Redis, Cassandra and MongoDB.
Justin Dearing presents a brief introduction to MongoDB, and focuses on interacting with it in Mono via the official 10gen driver. Techniques for handling business logic in application code, such as LINQ are discussed. This is a very code centric talk.
Thomas Risberg and Jared Rosoff show how to create Spring applications using Spring Data and MongoDB, applications deployed on Cloud Foundry.
Mat Wall makes a journey through Guardian’s online history, outlining technologies used – Perl/CGI, CMS, J2EE, Oracle-, and explaining why they chose a NoSQL solution – MongoDB - and its advantages.