Database Languages
A database system provides a data definition language to specify the database schema and a data manipulation language to express database queries and updates. In practice, the data definition and data manipulation languages are not two separate languages; instead they simply form parts of a single database language, such as the widely used SQL language.
Data-Definition Language
We specify a database schema by a set of definitions expressed by a special language called a data-definition language (DDL).
For instance, the following statement in the SQL language defines the account table:
create table account (account-number char(10), balance integer)
Execution of the above DDL statement creates the account table. In addition, it updates a special set of tables called the data dictionary or data directory.
A data dictionary contains metadata—that is, data about data. The schema of a table is an example of metadata. A database system consults the data dictionary before reading or modifying actual data.
We specify the storage structure and access methods used by the database system by a set of statements in a special type of DDL called a data storage and definition language. These statements define the implementation details of the database schemas, which are usually hidden from the users.
The data values stored in the database must satisfy certain consistency constraints. For example, suppose the balance on an account should not fall below $100. The DDL provides facilities to specify such constraints. The database systems check these constraints every time the database is updated.
Data-Manipulation Language
Data manipulation is
The retrieval of information stored in the database
The insertion of new information into the database
The deletion of information from the database
The modification of information stored in the database
A data-manipulation language (DML) is a language that enables users to access or manipulate data as organized by the appropriate data model. There are basically two types:
Procedural DMLs require a user to specify what data are needed and how to get those data.
Declarative DMLs (also referred to as nonprocedural DMLs) require a user to specify what data are needed without specifying how to get those data.
Declarative DMLs are usually easier to learn and use than are procedural DMLs. However, since a user does not have to specify how to get the data, the database system has to figure out an efficient means of accessing data. The DML component of the SQL language is nonprocedural.
A query is a statement requesting the retrieval of information. The portion of a DML that involves information retrieval is called a query language. Although technically incorrect, it is common practice to use the terms query language and data manipulation language synonymously.
This query in the SQL language finds the name of the customer whose customer-id is 192-83-7465:
select customer.customer-name
from customer
where customer.customer-id = 192-83-7465
The query specifies that those rows from the table customer where the customer-id is 192-83-7465 must be retrieved, and the customer-name attribute of these rows must be displayed.
Queries may involve information from more than one table. For instance, the following query finds the balance of all accounts owned by the customer with customerid 192-83-7465.
select account.balance
from depositor, account
where depositor.customer-id = 192-83-7465 and
depositor.account-number = account.account-number
There are a number of database query languages in use, either commercially or experimentally.
The levels of abstraction apply not only to defining or structuring data, but also to manipulating data. At the physical level, we must define algorithms that allow efficient access to data. At higher levels of abstraction, we emphasize ease of use. The goal is to allow humans to interact efficiently with the system. The query processor component of the database system translates DML queries into sequences of actions at the physical level of the database system.
