Paul King presents working with databases in Groovy, covering datasets, GMongo, Neo4J, raw JDBC, Groovy-SQL, CRUD, Hibernate, caching, Spring Data technologies, etc.
Tamar Bercovici presents Box’s transition from a single MySQL database to a fully sharded MySQL architecture, all the while serving 2 billion queries per day.
Peter Boros discusses a MySQL architecture useful for the majority of projects, backup, online schema changes, reliability and scalability issues, and basics of sharding.
Craig Brozefsky presents the tradeoffs involved with moving to a purely SQL relational model, instead of using an ORM, along with some of the tools built to facilitate this.
Charles Cai, Ashwani Roy discuss a robust, cost effective, hypothetical solution to address extreme challenges in financial institutions, from decision making support to pricing and risk management.
Yashwanth Nelapati and Marty Weiner share lessons learned growing Pinterest: sharding MySQL, caching, server management, all on Amazon EC2.
Kenneth M. Anderson shares some of the data modeling issues encountered while transitioning from a relational database to NoSQL.
Koa McCullough presents best practices for running Percona Server and MySQL in the cloud, cloud backups using EBS, Xtrabackup and S3, using Percona Toolkit to simplify operations, and XtraDB Cluster.
Eric Brewer takes a look at NoSQL’s history and considers what should be done so the current NoSQL solutions to evolve in order to address the full range of the application needs.
Zardosht Kasheff suggest using 3 rules for indexing SQL databases: Retrieve less data, Avoid point queries, and Avoid sorting.
Michael Stonebraker compares how RDBMS, NoSQL and NewSQL support today’s big data transaction processing needs. He also introduces VoltDB, an in-memory NewSQL database.
John Davies shares insight into SQL, NoSQL, grid, virtualization and caching technologies from his personal experience using them in financial institutions.