Relational Storage: SAS Data Sets
You can use SAS data sets, the default SAS storage format, to store data of any
granularity. The data values in a SAS data set are organized as a table of observations
(rows) and variables (columns). A SAS data set also contains descriptor information
such as the data types and lengths of the columns, as well as which SAS engine was
used to create the data.
Access to Third-Party Databases: SAS/ACCESS
SAS/ACCESS provides interfaces to a wide range of relational, hierarchical, and
network model databases. Examples include DB2, Oracle, SQL Server, Teradata,
Hadoop, IBM Information Management System (IMS), and Computer Associates
Integrated Database Management System (CA-IDMS). With SAS/ACCESS, SAS
Data Integration Studio and other SAS applications can read, write, and update data
regardless of which database and platform the data is stored on. SAS/ACCESS
interfaces provide fast, efficient data loading and enable SAS applications to work
directly from your data sources without making a copy.
High-Performance Computing: SAS In-Database
To support high-performance computing for complex, high-volume analytics, SAS
In-Database enables certain data management, analytic, and reporting tasks to be
performed inside the database. In-database technology minimizes the movement of
data across the network, while enabling more sophisticated queries and producing
results more quickly. This technology is available for several types of databases.
Multidimensional Storage: SAS OLAP Server
The SAS OLAP Server provides dedicated storage for data that has been
summarized along multiple business dimensions. The server uses a threaded,
scalable, and open technology and is especially designed for fast-turnaround
processing and reporting.
A simplified ETL process enables you to build consistent OLAP cubes from
disparate systems. A threaded query engine and parallel storage enable data to be
spread across multiple-disk systems. Support is provided for multidimensional
(MOLAP) and hybrid (HOLAP) data stores, as well as for open industry standards.
Parallel Storage: SAS Scalable Performance Data Engine and SAS Scalable
Performance Data Server
The SAS SPD Engine and SAS SPD Server provide a high-speed data storage
alternative for processing very large SAS data sets. They read and write tables that
contain millions of observations, including tables that exceed the 2-GB size limit
imposed by some operating systems. In addition, they provide the rapid data access
that is needed to support intensive processing by SAS analytic software and
These facilities work by organizing data into a streamlined file format and then using
threads to read blocks of data very rapidly and in parallel. The software tasks are
performed in conjunction with an operating system that enables threads to execute on
any of the CPUs that are available on a machine.
The SAS SPD Engine, which is included with Base SAS software, is a single-user
data storage solution. The SAS SPD Server, which is available as a separate product,
is a multi-user solution that includes a comprehensive security infrastructure, backup
and restore utilities, and sophisticated administrative and tuning options.
The software tools in the business intelligence category address two main functional
areas: information design, and self-service reporting and analysis.
Components of the SAS Intelligence Platform 5