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Computer Science
Computer Catlog
Oracle Catlog

History of Oracle
Introduction to Terms
Oracle Configurations
Roles of Database Administrator
Oracle Architecture
A Brief History of SQL
Dr. Codd's 12 Rules
An Overview of SQL
The SELECT Statement
Expressions, Conditions, and Operators
Functions
Clauses in SQL
Joining Tables
Sub Query
Manipulating Data
Building a Database
Views and Indexes
Controlling Transactions
Database Security
Advanced SQL Topics
Cursors
Stored Procedures
Triggers
Embedded SQL
SQL Tuning
Using Views in Data Dictionary
Using SQL to Generate SQL Statements

Oracle Configurations


    There are many different types of Oracle configurations and uses. Let's look at some of these different types of systems and analyze their usage and characteristics.

OLTP


    The Online Transaction Processing (OLTP) system is probably the most common of the RDBMS configurations. OLTP systems have online users that access the system. These systems are typically used for order-entry purposes, such as for retail sales, credit-card validation, ATM transactions, and so on.

Characteristics of OLTP Systems


    OLTP systems typically support large numbers of online users simultaneously accessing the RDBMS. Because users are waiting for data to be returned to them, any excessive response time is immediately noticeable. OLTP systems are characteristically read and write intensive. Depending on the specific application, this read/write ratio might vary.


DSS


    The Decision Support System (DSS) is used to assist with the decision-making process. These decisions might be based on information such as how sales in a particular region are doing, what cross-section of customers is buying a particular product, or to whom to send a mailing. The DSS system is used to help make decisions by providing good data.

Characteristics of a DSS


    The DSS is characterized by long-running queries against a large set of data. Unlike the OLTP system, where users are waiting for data to return to them online, here users expect the queries to take minutes, hours, or days to complete. The data is typically generated from a different source and loaded onto the DSS computer in bulk. Except for during the load, the DSS system is characterized by being read intensive (with very few writes).

Data Warehouse


    A data warehouse is typically considered to be a large-scale system that consists of both DSS and OLTP components. These systems are typically hundreds of gigabytes in size and support many users.

Characteristics of a Data Warehouse


    Data warehouses have some of the attributes of a DSS system, such as long-running queries and a possible online component. In many cases, this component is the source of the data used in the DSS queries.

Data Mart


    A data mart, which is a smaller-scale version of a data warehouse, serves many of the same functions as a data warehouse.

Characteristics of a Data Mart


    A data mart is typically 100GB or less in size. As with a data warehouse, a data mart supports many online users as well as a decision-support function.

Video Server


    A video server can support large numbers of video data streams. These video streams can be used for purposes such as video on demand for entertainment as well as training functions.

Characteristics of a Video Server


    The video server system must support a high network bandwidth in order to support multiple data streams. The video server must also be able to support a high I/O bandwidth. These disk accesses are typically of a very large block size and sequential in nature.


Web Server


    The Oracle Web server is designed to support both static and dynamic Web pages. These pages can be simple Web pages or complex database-generated pages. Oracle Web server systems are also typically used in Web commerce applications. These installations can allow the customer to browse online catalogs, which might feature graphics or even video. The customer can then purchase items online.

Characteristics of an Oracle Web Server


    The Oracle Web server typically supports many online users. There is typically a large amount of data that has been accessed frequently and other data that is less frequently accessed. A large amount of memory can help improve performance in this type of configuration.

OLAP


    The term OLAP (Online Analytical Processing) is usually used in relation with multidimensional data. OLAP users might be financial analysts or marketing personnel looking at global data.

Characteristics of an OLAP System


    An OLAP system typically involves a large amount of disk space with heavy I/O and memory requirements. An OLAP system might support only a few or many users. This depends on your type of configuration.