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Architectures for scaling out
The two distinct approaches to scaling out database management systems are
are generally referred to as a shared architecture and a shared-nothing
architecture. Both architectures attempt to achieve the same goal, which is to
implement a database management system that consists of a cluster of servers,
provides linear scalability, and appears as single database to the end users.
A
shared architecture
attempts to accomplish this goal while sharing the
database. As more servers are added to the system, they all share or attempt to
share the same database, which resides on shared storage, hence the name
shared architecture. Oracle is an example of a database application that
implements a shared-disk approach.
A
shared-nothing architecture
database into smaller and more manageable parts, called partitions. The term
shared-nothing simply refers to the fact that as more servers are added to the
system, each server manages a clearly defined portion of the database. The fact
that the database is partitioned should not imply that the system cannot be
implemented on shared storage. IBM DB2 and Microsoft SQL Server both
implement a shared-nothing approach.
Choosing scale-up or scale-out
Microsoft SQL Server 2005 and SQL Server 2008 are well-suited for scale-up
configurations, such as a multinode x3950 M2 configuration. It follows a single
server, shared-nothing approach and it is a high performance solution for
Windows environments.
Oracle uses a shared-disk approach and is suited to scale-up or scale-out. It is a
leading solution for middle market UNIX®, Windows, and Linux environments.
Scale-out capabilities can be extended with Oracle 9i or 10g RAC.
DB2 is suited to scale-up or scale-out. It is developed following a multi-server,
shared nothing approach, and is the highest performing database environment
for mainframe, UNIX, and Linux environments.
Scale-up is preferred for smaller databases (150-200 GB). For larger databases,
large block I/O, data warehousing and decision support applications, use a
scale-out deployment.
accomplishes the same goal by dividing a large
Chapter 2. Product positioning
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