Oracle9i RAC vs DB2 UDB EEE: A Technical Comparison

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本文档是一份由Oracle发布的白皮书，对比了Oracle9i Real Application Clusters (RAC)与IBM DB2 Universal Database Enterprise Edition (UDB EEE) v7.2的技术特性。该比较旨在帮助IT专业人员在选择这两种数据库解决方案时做出决策。 **执行概览（Executive Overview）** 白皮书首先概述了主要的比较点，包括RAC和DB2 UDB EEE在关键性能、可扩展性和应用支持方面的区别。它强调了在高并发事务处理（OLTP）和决策支持系统（DSS）工作负载中的性能比较。 **硬件要求** 讨论了两种数据库在集群互联（Cluster Interconnect）、存储方式（如共享磁盘与共享无数据存储）以及与传统架构（如Oracle的传统共享无数据模式与DB2的共享数据模式）的差异。例如，RAC通过共享缓存技术提供更高的性能，而DB2的Parallel Sysplex Shared-Data模型也有所侧重。 **软件需求** 接下来详述了系统软件要求，包括部署策略，如数据分区（Oracle的Data Partitioning与DB2 EEE的分区机制）。选择合适的分区键（Partition Key）是关键，文中提到了相应的考虑因素。 **可扩展性和性能** 性能部分深入分析了在OLTP应用程序中的表现，比如数据探查（Partition Probes）、数据缓存和两阶段提交（Two-phase Commit）的优化。白皮书还探讨了如何处理负载不均衡（Load Skew）以及事务路由（Transaction Routing），以确保系统的稳定运行。对于DSS应用，RAC的优势在于其在复杂OLTP场景下的处理能力和对大数据分析的支持。此外，文章还讨论了RAC在大规模环境下的可扩展性，如在TPC-C合成基准测试（TPC-CSynthetic Benchmarks）中的表现。 **包装应用与复杂OLTP** 针对那些包含复杂OLTP操作的预包装应用程序，RAC的并行处理能力被强调，因为它能够更好地处理这些业务场景。 **总结** 这份技术比较提供了详尽的评估，帮助用户理解Oracle9i RAC与DB2 UDB EEE v7.2在不同场景下的优劣，以便根据组织的具体需求做出明智的决策。对于那些寻求高度可用性、性能和可扩展性的企业，这份文档是重要的参考资源。

Technical Comparison of Oracle9i Real Application Clusters vs. IBM DB2 UDB EEE v7.2 Page 6

• How will the application architecture (OLTP, DSS) affect the database

performance?

• How much re-training will administrators need to support operations?

With only two real parallel database choices to pick from, Oracle9i Real

Application Clusters and IBM’s DB2 Universal Database EEE V7.2, the choice

should be easy.

INTRODUCTION

The focus of this paper is to compare the deployment of a real world

application in a cluster environment of Oracle9i Real Application Clusters ( RAC

) and IBM’s DB2 Universal Database EEE V7.2 ( DB2 EEE ) parallel database.

The reason for this focus is two fold. First, both databases have many features

so we need to limit the scope of this paper to where both products compete.

And secondly, if you are addressing the needs of today’s IT environments,

reliability, availability and scalability through modular growth, then clustering is

the only solution that will provide a cost effective solution.

We will first look at the hardware and software platforms to see how they

measure up, and what, if any, special requirements are needed, as well as the

costs that are associated with them. Next, we will look at the deployment of

the application and what it takes to roll out a production system. Once the

application is up and running, performance becomes the top priority of the data

center. We will break this down into three environments, OLTP, DSS and

packaged application because they have different requirements and

characteristics that need to be addressed.

We can first note that the hardware and software requirements are similar. The

abstraction to the application is also the same with both solutions - it gives an

illusion of a single database and there is no need to modify the SQL code. The

differences are in ease of deployment, performance and manageability.

First, let’s clarify some definitions and terminology that we will use.

In DB2 terminology, the term partition is used to refer to a logical node and the

data that is owned by the logical node. This usage is different from the RAC

usage where a partition refers to a part of a table or index. In this document, we

use the word partition to mean a logical node (i.e, the DB2 usage). Each

partition has its own buffer pool, package cache etc. It may be convenient to

think of a partition as equivalent to an Oracle instance except that it can access

only a subset of the data directly.

HARDWARE REQUIREMENTS

Both databases have similar cluster hardware requirements. A cluster is a group

of independent servers that collaborate as a single system. The primary cluster

components are processor nodes, a cluster interconnect (private network), and

Technical Comparison of Oracle9i Real Application Clusters vs. IBM DB2 UDB EEE v7.2 Page 7

a disk subsystem. The clusters share disk access and resources that manage the

data, but each distinct hardware cluster nodes do not share memory. Each

node has its own dedicated system memory as well as its own operating

system, database instance, and application software as seen in Figure 1.

Clusters can provide improved fault resilience and modular incremental system

growth over single symmetric multi-processors systems. In the event of sub-

system failures, clustering ensures high availability. Redundant hardware

components, such as additional nodes, interconnects, and shared disks, provide

higher availability. Such redundant hardware architectures avoid single points-

of-failure and provide exceptional fault resilience.

From a conceptual view, the cluster requirements for RAC and DB2 are similar,

especially when high availability (HA) is a basic requirement. In a cluster, CPU

and memory requirements for each node are similar to single systems

requirements and leave no differentiation for this discussion. However, there

has been a lot of debate on the other cluster components requirements,

especially around performance and costs. The two relevant requirements are:

• Cluster Interconnect

• Shared disk vs. shared-nothing storage

Cluster Interconnect

Each node in a cluster needs to keep other nodes in that cluster informed of its

health and configuration. This is done periodically by broadcasting a network

message, called a heartbeat, across a network. The heartbeat signal is usually

sent over a private network, the cluster interconnect, which is used for inter-

node communications.

This cluster interconnect is built by installing network cards in each node and

connecting them by an appropriate network cable and configuring a software

protocol to run across the wire. This interconnect can be a low cost Ethernet

Computer

Interconnect

Shared Storage System

Figure 1: A Cluster Comprises Processor Nodes, Cluster

Interconnect, and Disk Subsystem

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