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.
Oracle has today released version 3.7 of Coherence, its distributed in-memory data grid. The new product introduces a feature called Elastic Data. According to Cameron Purdy, Vice President of Development for the Coherence product, this allows near memory speed access to data, regardless of storage medium.
The Apache Software Foundation has selected the Object Oriented Data Technology architecture to become one of its Top-Level-Projects (TLP). Originally created by NASA’s Jet Propulsion Laboratory, Pasadena, OODT allows transparent integration of geographically distributed and disparate computing and data resources via metadata middleware.
In Part 1 of this series we introduced a design pattern for grid computing on Azure, while in Part 2 we developed a grid application in C#. This time we'll run the application, first locally and then in the cloud. In order to do that, we'll need some help from a grid computing framework.
David Pallmann shows how to perform grid computations on the Azure cloud computing platform. In Part 1 he presented a design pattern, while in Part 2&3 he shows how to develop&run a grid application.
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.
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.
What is Data Grid computing? What makes it different from a database? Is a data grid always scalable? Is the cloud the next step? Cameron Purdy answered these questions and others during an InfoQ interview, and also gave some hints on how to build scalable grids and how to avoid horror stories.
In this interview from QCon San Francisco 2007, Randy Shoup discusses the architecture of eBay. Topics discussed include eBay's architectural principles, horizontal and vertical partitioning, ACID vs. BASE, handling data inconsistency, distributed caching, updating eBay on the fly, architectural and coding standards, eBay's search infrastructure, grid computing, and SOA.
