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League of Legends: Scaling to Millions of Ninjas, Yordles, and Wizards

Posted by Scott Delap and Randy Stafford  on  Apr 07, 2011 2

Scott Delap and Randy Stafford explain the architectural decisions made in order to scale, monitor and operate 24/7 the game League of Legends, bringing insight on how they use Oracle Coherence for that.

Evolving the Key/Value Programming Model to a Higher Level

Posted by Billy Newport  on  Jan 19, 2010 6

In this presentation from QCon San Francisco 2009, Billy Newport discusses the ways that developers interact with key/value (KV) stores such as memcached and WebSphere eXtreme Scale, entity vs column-oriented approaches, synchronous and asynchronous operations, large data sets, using a DBMS as a column store, collocating closures and data, and features that could be added to increase scalability.

Data Grid Design Patterns

Posted by Brian Oliver  on  Nov 04, 2009

Brian Oliver explains a number of data grid design patters: Command, Functor, Store and Forward Messaging, and Push Replication. He also mentions some traditional patterns used so far and Coherence Incubator, a repository for design patterns reference implementations.

An Introduction to Data Grids

Posted by Cameron Purdy  on  Oct 10, 2009 1

Cameron Purdy explains how a data grid functions by using a partition topology for data access, update, recovery and local storage, accessing data using read/write-through and write behind, and invoking operations through Observable, QueryMap and InvocableMap interfaces. He also offers some examples of data grids solving complex problems and introduces Coherence, Oracle’s data grid solution.

Transforming the Reconciliation Process

Posted by Brian Oliver  on  Sep 23, 2009

Brian Oliver explains what the Reconciliation Process is, why the current approach to reconciliation based on client-server is no longer suitable and how data grids and event based reconciliation might help.

Distributed Caching Essential Lessons

Posted by Cameron Purdy  on  Jan 09, 2007 3

In this presentation, recorded at Javapolis, Cameron Purdy shows how to improve application performance & scalability via caching architectures to reduce load on the database tier and & clustered caching to provide transparent fail-over by reliably sharing live data among clustered JVMs.

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