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Using DataDirect Connect for Oracle with Oracle RAC
Introduction
In today's e-business on-demand environment, more companies are turning to a Grid computing infrastructure for distributed computing and data resources such as processing, network bandwidth, and storage. Grids allow companies to pool available resources for scalability and high availability. Built on Oracle Parallel Server (OPS) architecture, Oracle introduced Real Application Clusters (RAC) with Oracle 9i. Oracle RAC also is a key part of the Oracle 10g release. Oracle RAC allows a single physical Oracle database to be accessed by concurrent instances of Oracle running across several different CPUs.
An Oracle RAC system is composed of a group of independent servers, or nodes, that cooperate as a single system as shown in Figure 1. These nodes have a single view of the distributed cache memory for the entire database system.
Figure 1: Oracle RAC System
A cluster architecture, such as Oracle RAC, provides applications access to more horsepower when needed, while allowing computing resources to be used for other applications when database resources are not as heavily required. For example, in the event of a sudden increase in traffic, an Oracle RAC system can distribute the load over many nodes, a feature referred to as load balancing.
In addition, an Oracle RAC system can protect against computer failures caused by unexpected hardware failures and operating system or server crashes, as well as processing loss caused by planned maintenance. When a node failure occurs, connection attempts can fail over to other nodes in the cluster, which assume the work of the failed node. When connection failover occurs and a service connection is redirected to another node, users can continue to access the service, unaware that it is now provided from a different node.
This document explains how you can take advantage of Oracle RAC features such as load balancing and connection failover using the DataDirect Connect® for ODBC Oracle drivers to connect your data critical applications to data.
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