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Relational databases are the underlying engines that provide power to
data warehouses. Many of the characteristics and features that have been
developed and enhanced to make relational databases the workhorses of
online transactional processing (OLTP) systems are directly applicable
to data warehouses.
Relational databases are used in data warehouse systems to stage,
cleanse, and transform incoming data in the data preparation database,
contain and manage the massive quantities of data in the data warehouse
database, and support data marts.
Data warehouses store, manage, and manipulate huge quantities of
data, often on the order of hundreds of millions of rows of historical
information. The relational database must provide rapid data transfer
and update, flexible and efficient indexing, and sophisticated and
effective query capabilities to organize and retrieve data warehouse
data. Sophisticated locking mechanisms and high multi-table transaction
throughput may be more important in OLTP systems than in data
warehouses, but such features are often based on extremely efficient
relational engine design, which is very important in data warehouse
operations.
Microsoft® SQL Server™ 2000 provides an extremely powerful
relational database for OLTP systems and data warehouse data storage. It
also includes many powerful features critical to data warehouses, such
as Data Transformation Services (DTS), replication management, SQL
Server 2000 Analysis Services with its multidimensional online
analytical processing (OLAP) and data mining server and management
support, SQL Server 2000 Meta Data Services, and English Query for
natural language querying of both relational and multidimensional data.
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