Stuart Sierra provides an introduction to Datomic's data model, architecture, query syntax, and transactions.
Brett Meyer demos using multiple-tenancy, geographic data, auditing/versioning, sharding, OSGi, and integration with Hibernate.
Craig Andera explains Datomic from the perspective gained in implementing and optimizing a real-world production system, detailing the Datomic indexing process.
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.
John Davies walks through a reference implementation of a in-memory database meant to combine dozens of different legacy databases developed by banks over time.
Yashwanth Nelapati and Marty Weiner share lessons learned growing Pinterest: sharding MySQL, caching, server management, all on Amazon EC2.
Ori Herrnstadt introduces the Akiban database which solves the problem of joins and combines the best of relational and document databases.
Chris Haddad discusses cloud computing, PaaS, multi-tenancy, cloud ecosystems, cloud aware APIs from the perspective and the benefits it can provide to the business.
Neha Narula provides advice on choosing a data store for a web applications and executing distributed queries.
Rich Hickey deconstructs the monolithic database into separate services, transactions, storage, query, combining them with a data model based on atomic facts to provide new capabilities and tradeoffs.
Zardosht Kasheff suggest using 3 rules for indexing SQL databases: Retrieve less data, Avoid point queries, and Avoid sorting.