Database System Concepts and Architecture
2.1 Data Models, Schemas, and Instances
● Data abstraction generally refers to the suppression of details of data
organization and storage, and the highlighting of the essential features for an
improved understanding of data.
● One of the main characteristics of the database approach is to support data
abstraction so that different users can perceive data at their preferred level of
detail.
● A data model—a collection of concepts that can be used to describe the
structure of a database.
● By structure of a database we mean the data types, relationships, and
constraints that apply to the data.
● Most data models also include a set of basic operations for specifying
retrievals and updates on the database.
2.1.1 Categories of Data Models
● We can categorize according to the types of concepts they use to describe
the database structure.
● High-level or conceptual data models provide concepts that are close to the
way many users perceive data.
● low-level or physical data models provide concepts that describe the details
of how data is stored on the computer storage media.
● Concepts provided by physical data models are generally meant for
computer specialists, not for end users.
● Between these two extremes is a class of Representational (or
implementation) data models.
● Representational data models hide many details of data storage on disk but
can be implemented on a computer system directly.
Conceptual data models
● Conceptual data models use concepts such as entities, attributes, and
relationships.
● An entity represents a real-world object or concept, such as an employee or a
project
● An attribute represents some property of interest that further describes an
entity, such as the employee’s name or salary.
, ● A relationship among two or more entities represents an association among
the entities, for example, a works-on relationship between an employee and
a project.
Representational or implementation data models
● Representational or implementation data models are the models used most
frequently in traditional commercial DBMSs.
● These include the widely used relational data model, as well as the so-called
legacy data models—the network and hierarchical models
● Representational data models represent data by using record structures and
hence are sometimes called record-based data model.
object data model
● the object data model is an example of a new family of higher-level
● Implementation data models are closer to conceptual data models.
● A standard for object databases called the ODMG object model has
been proposed by the Object Data Management Group (ODMG).
● Object data models are also frequently utilized as high-level
conceptual models, particularly in the software engineering domain.
Physical data models
● Physical data models describe how data is stored as files in the
computer by representing information such as record formats, record
orderings, and access paths.
● Access path is a search structure that makes the search for particular
database records efficient, such as indexing or hashing.
● An index is an example of an access path that allows direct access to
data using an index term or a keyword.
Self-describing data models.
● Another class of data models is known as self-describing data
models. The data storage in systems based on these models combines
the description of the data with the data values themselves.
● In traditional DBMSs, the description (schema) is separated from the
data. These models include XML as well as many of the key-value
stores and NOSQL systems that were recently created for managing
big data.
2.1.2 Schemas, Instances, and Database State
● The description of a database is called the database schema, which is
specified during database design and is not expected to change frequently
● A displayed schema is called a schema diagram. The diagram displays the
structure of each record type but not the actual instances of records.
2.1 Data Models, Schemas, and Instances
● Data abstraction generally refers to the suppression of details of data
organization and storage, and the highlighting of the essential features for an
improved understanding of data.
● One of the main characteristics of the database approach is to support data
abstraction so that different users can perceive data at their preferred level of
detail.
● A data model—a collection of concepts that can be used to describe the
structure of a database.
● By structure of a database we mean the data types, relationships, and
constraints that apply to the data.
● Most data models also include a set of basic operations for specifying
retrievals and updates on the database.
2.1.1 Categories of Data Models
● We can categorize according to the types of concepts they use to describe
the database structure.
● High-level or conceptual data models provide concepts that are close to the
way many users perceive data.
● low-level or physical data models provide concepts that describe the details
of how data is stored on the computer storage media.
● Concepts provided by physical data models are generally meant for
computer specialists, not for end users.
● Between these two extremes is a class of Representational (or
implementation) data models.
● Representational data models hide many details of data storage on disk but
can be implemented on a computer system directly.
Conceptual data models
● Conceptual data models use concepts such as entities, attributes, and
relationships.
● An entity represents a real-world object or concept, such as an employee or a
project
● An attribute represents some property of interest that further describes an
entity, such as the employee’s name or salary.
, ● A relationship among two or more entities represents an association among
the entities, for example, a works-on relationship between an employee and
a project.
Representational or implementation data models
● Representational or implementation data models are the models used most
frequently in traditional commercial DBMSs.
● These include the widely used relational data model, as well as the so-called
legacy data models—the network and hierarchical models
● Representational data models represent data by using record structures and
hence are sometimes called record-based data model.
object data model
● the object data model is an example of a new family of higher-level
● Implementation data models are closer to conceptual data models.
● A standard for object databases called the ODMG object model has
been proposed by the Object Data Management Group (ODMG).
● Object data models are also frequently utilized as high-level
conceptual models, particularly in the software engineering domain.
Physical data models
● Physical data models describe how data is stored as files in the
computer by representing information such as record formats, record
orderings, and access paths.
● Access path is a search structure that makes the search for particular
database records efficient, such as indexing or hashing.
● An index is an example of an access path that allows direct access to
data using an index term or a keyword.
Self-describing data models.
● Another class of data models is known as self-describing data
models. The data storage in systems based on these models combines
the description of the data with the data values themselves.
● In traditional DBMSs, the description (schema) is separated from the
data. These models include XML as well as many of the key-value
stores and NOSQL systems that were recently created for managing
big data.
2.1.2 Schemas, Instances, and Database State
● The description of a database is called the database schema, which is
specified during database design and is not expected to change frequently
● A displayed schema is called a schema diagram. The diagram displays the
structure of each record type but not the actual instances of records.
