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Database System Concepts, 5th Ed.
©Silberschatz, Korth and Sudarshan
See www.db-book.com for conditions on re-use
Chapter 1: IntroductionChapter 1: Introduction
©Silberschatz, Korth and Sudarshan1.2atabase System Concepts - 5th
Edition, May 23, 2005
Chapter 1: IntroductionChapter 1: Introduction
Purpose of Database Systems
Database Languages
Relational Databases
Database Design
Data Models
Database Internals
Database Users and Administrators
Overall Structure
History of Database Systems
©Silberschatz, Korth and Sudarshan1.3atabase System Concepts - 5th
Edition, May 23, 2005
Database Management SystemDatabase Management System
(DBMS)(DBMS)
DBMS contains information about a particular enterprise
Collection of interrelated data
Set of programs to access the data
An environment that is both convenient and efficient to use
Database Applications:
Banking: all transactions
Airlines: reservations, schedules
Universities: registration, grades
Sales: customers, products, purchases
Online retailers: order tracking, customized recommendations
Manufacturing: production, inventory, orders, supply chain
Human resources: employee records, salaries, tax deductions
Databases touch all aspects of our lives
©Silberschatz, Korth and Sudarshan1.4atabase System Concepts - 5th
Edition, May 23, 2005
Purpose of Database SystemsPurpose of Database Systems
In the early days, database applications were built directly on top of
file systems
Drawbacks of using file systems to store data:
Data redundancy and inconsistency
 Multiple file formats, duplication of information in different files
Difficulty in accessing data
 Need to write a new program to carry out each new task
Data isolation — multiple files and formats
Integrity problems
 Integrity constraints (e.g. account balance > 0) become
“buried” in program code rather than being stated explicitly
 Hard to add new constraints or change existing ones
©Silberschatz, Korth and Sudarshan1.5atabase System Concepts - 5th
Edition, May 23, 2005
Purpose of Database SystemsPurpose of Database Systems
(Cont.)(Cont.)
Drawbacks of using file systems (cont.)
Atomicity of updates
 Failures may leave database in an inconsistent state with partial
updates carried out
 Example: Transfer of funds from one account to another should
either complete or not happen at all
Concurrent access by multiple users
 Concurrent accessed needed for performance
 Uncontrolled concurrent accesses can lead to inconsistencies
– Example: Two people reading a balance and updating it at the
same time
Security problems
 Hard to provide user access to some, but not all, data
Database systems offer solutions to all the above problems
©Silberschatz, Korth and Sudarshan1.6atabase System Concepts - 5th
Edition, May 23, 2005
Levels of AbstractionLevels of Abstraction
Physical level: describes how a record (e.g., customer) is stored.
Logical level: describes data stored in database, and the relationships
among the data.
type customer = record
customer_id : string;
customer_name : string;
customer_street : string;
customer_city : string;
end;
View level: application programs hide details of data types. Views can
also hide information (such as an employee’s salary) for security
purposes.
©Silberschatz, Korth and Sudarshan1.7atabase System Concepts - 5th
Edition, May 23, 2005
View of DataView of Data
An architecture for a database system
©Silberschatz, Korth and Sudarshan1.8atabase System Concepts - 5th
Edition, May 23, 2005
Instances and SchemasInstances and Schemas
Similar to types and variables in programming languages
Schema – the logical structure of the database
Example: The database consists of information about a set of customers and
accounts and the relationship between them)
Analogous to type information of a variable in a program
Physical schema: database design at the physical level
Logical schema: database design at the logical level
Instance – the actual content of the database at a particular point in time
Analogous to the value of a variable
Physical Data Independence – the ability to modify the physical schema without
changing the logical schema
Applications depend on the logical schema
In general, the interfaces between the various levels and components should be
well defined so that changes in some parts do not seriously influence others.
©Silberschatz, Korth and Sudarshan1.9atabase System Concepts - 5th
Edition, May 23, 2005
Data ModelsData Models
A collection of tools for describing
Data
Data relationships
Data semantics
Data constraints
Relational model
Entity-Relationship data model (mainly for database design)
Object-based data models (Object-oriented and Object-relational)
Semistructured data model (XML)
Other older models:
Network model
Hierarchical model
©Silberschatz, Korth and Sudarshan1.10atabase System Concepts - 5th
Edition, May 23, 2005
Data Manipulation Language (DML)Data Manipulation Language (DML)
Language for accessing and manipulating the data organized by the
appropriate data model
DML also known as query language
Two classes of languages
Procedural – user specifies what data is required and how to get
those data
Declarative (nonprocedural) – user specifies what data is
required without specifying how to get those data
SQL is the most widely used query language
©Silberschatz, Korth and Sudarshan1.11atabase System Concepts - 5th
Edition, May 23, 2005
Data Definition Language (DDL)Data Definition Language (DDL)
Specification notation for defining the database schema
Example: create table account (
account_number char(10),
branch_name char(10),
balance integer)
DDL compiler generates a set of tables stored in a data dictionary
Data dictionary contains metadata (i.e., data about data)
Database schema
Data storage and definition language
 Specifies the storage structure and access methods used
Integrity constraints
 Domain constraints
 Referential integrity (e.g. branch_name must correspond to a
valid branch in the branch table)
Authorization
©Silberschatz, Korth and Sudarshan1.12atabase System Concepts - 5th
Edition, May 23, 2005
Relational ModelRelational Model
Example of tabular data in the relational model
Attributes
©Silberschatz, Korth and Sudarshan1.13atabase System Concepts - 5th
Edition, May 23, 2005
A Sample Relational DatabaseA Sample Relational Database
©Silberschatz, Korth and Sudarshan1.14atabase System Concepts - 5th
Edition, May 23, 2005
SQLSQL
SQL: widely used non-procedural language
Example: Find the name of the customer with customer-id 192-83-7465
select customer.customer_name
from customer
where customer.customer_id = ‘192-83-7465’
Example: Find the balances of all accounts held by the customer with
customer-id 192-83-7465
select account.balance
from depositor, account
where depositor.customer_id = ‘192-83-7465’ and
depositor.account_number = account.account_number
Application programs generally access databases through one of
Language extensions to allow embedded SQL
Application program interface (e.g., ODBC/JDBC) which allow SQL
queries to be sent to a database
©Silberschatz, Korth and Sudarshan1.15atabase System Concepts - 5th
Edition, May 23, 2005
Database DesignDatabase Design
The process of designing the general structure of the database:
Logical Design – Deciding on the database schema. Database design
requires that we find a “good” collection of relation schemas.
Business decision – What attributes should we record in the
database?
Computer Science decision – What relation schemas should we
have and how should the attributes be distributed among the various
relation schemas?
Physical Design – Deciding on the physical layout of the database
©Silberschatz, Korth and Sudarshan1.16atabase System Concepts - 5th
Edition, May 23, 2005
The Entity-Relationship ModelThe Entity-Relationship Model
Models an enterprise as a collection of entities and relationships
Entity: a “thing” or “object” in the enterprise that is distinguishable
from other objects
 Described by a set of attributes
Relationship: an association among several entities
Represented diagrammatically by an entity-relationship diagram:
©Silberschatz, Korth and Sudarshan1.17atabase System Concepts - 5th
Edition, May 23, 2005
Other Data ModelsOther Data Models
Object-oriented data model
Object-relational data model
©Silberschatz, Korth and Sudarshan1.18atabase System Concepts - 5th
Edition, May 23, 2005
Database Application ArchitecturesDatabase Application Architectures
(web browser)
Old Modern
©Silberschatz, Korth and Sudarshan1.19atabase System Concepts - 5th
Edition, May 23, 2005
Database Management SystemDatabase Management System
InternalsInternals
Storage management
Query processing
Transaction processing
©Silberschatz, Korth and Sudarshan1.20atabase System Concepts - 5th
Edition, May 23, 2005
Storage ManagementStorage Management
Storage manager is a program module that provides the interface
between the low-level data stored in the database and the application
programs and queries submitted to the system.
The storage manager is responsible to the following tasks:
Interaction with the file manager
Efficient storing, retrieving and updating of data
Issues:
Storage access
File organization
Indexing and hashing
©Silberschatz, Korth and Sudarshan1.21atabase System Concepts - 5th
Edition, May 23, 2005
Query ProcessingQuery Processing
1. Parsing and translation
2. Optimization
3. Evaluation
©Silberschatz, Korth and Sudarshan1.22atabase System Concepts - 5th
Edition, May 23, 2005
Query Processing (Cont.)Query Processing (Cont.)
Alternative ways of evaluating a given query
Equivalent expressions
Different algorithms for each operation
Cost difference between a good and a bad way of evaluating a query can
be enormous
Need to estimate the cost of operations
Depends critically on statistical information about relations which the
database must maintain
Need to estimate statistics for intermediate results to compute cost of
complex expressions
©Silberschatz, Korth and Sudarshan1.23atabase System Concepts - 5th
Edition, May 23, 2005
Transaction ManagementTransaction Management
A transaction is a collection of operations that performs a single
logical function in a database application
Transaction-management component ensures that the database
remains in a consistent (correct) state despite system failures (e.g.,
power failures and operating system crashes) and transaction failures.
Concurrency-control manager controls the interaction among the
concurrent transactions, to ensure the consistency of the database.
©Silberschatz, Korth and Sudarshan1.24atabase System Concepts - 5th
Edition, May 23, 2005
Overall System StructureOverall System Structure
©Silberschatz, Korth and Sudarshan1.25atabase System Concepts - 5th
Edition, May 23, 2005
History of Database SystemsHistory of Database Systems
1950s and early 1960s:
Data processing using magnetic tapes for storage
 Tapes provide only sequential access
Punched cards for input
Late 1960s and 1970s:
Hard disks allow direct access to data
Network and hierarchical data models in widespread use
Ted Codd defines the relational data model
 Would win the ACM Turing Award for this work
 IBM Research begins System R prototype
 UC Berkeley begins Ingres prototype
High-performance (for the era) transaction processing
©Silberschatz, Korth and Sudarshan1.26atabase System Concepts - 5th
Edition, May 23, 2005
History (cont.)History (cont.)
1980s:
Research relational prototypes evolve into commercial systems
 SQL becomes industry standard
Parallel and distributed database systems
Object-oriented database systems
1990s:
Large decision support and data-mining applications
Large multi-terabyte data warehouses
Emergence of Web commerce
2000s:
XML and XQuery standards
Automated database administration
Increasing use of highly parallel database systems
Web-scale distributed data storage systems
Database System Concepts, 5th Ed.
©Silberschatz, Korth and Sudarshan
See www.db-book.com for conditions on re-use
End of Chapter 1End of Chapter 1
©Silberschatz, Korth and Sudarshan1.28atabase System Concepts - 5th
Edition, May 23, 2005
Database UsersDatabase Users
Users are differentiated by the way they expect to interact with
the system
Application programmers – interact with system through DML calls
Sophisticated users – form requests in a database query language
Specialized users – write specialized database applications that do
not fit into the traditional data processing framework
Naï ve users – invoke one of the permanent application programs
that have been written previously
Examples, people accessing database over the web, bank tellers,
clerical staff
©Silberschatz, Korth and Sudarshan1.29atabase System Concepts - 5th
Edition, May 23, 2005
Database AdministratorDatabase Administrator
Coordinates all the activities of the database system
has a good understanding of the enterprise’s information resources
and needs.
Database administrator's duties include:
Storage structure and access method definition
Schema and physical organization modification
Granting users authority to access the database
Backing up data
Monitoring performance and responding to changes
 Database tuning
©Silberschatz, Korth and Sudarshan1.30atabase System Concepts - 5th
Edition, May 23, 2005
Database ArchitectureDatabase Architecture
The architecture of a database systems is greatly influenced by
the underlying computer system on which the database is running:
Centralized
Client-server
Parallel (multiple processors and disks)
Distributed
©Silberschatz, Korth and Sudarshan1.31atabase System Concepts - 5th
Edition, May 23, 2005
Object-Relational Data ModelsObject-Relational Data Models
Extend the relational data model by including object orientation and
constructs to deal with added data types.
Allow attributes of tuples to have complex types, including non-atomic
values such as nested relations.
Preserve relational foundations, in particular the declarative access to
data, while extending modeling power.
Provide upward compatibility with existing relational languages.
©Silberschatz, Korth and Sudarshan1.32atabase System Concepts - 5th
Edition, May 23, 2005
XML: Extensible Markup LanguageXML: Extensible Markup Language
Defined by the WWW Consortium (W3C)
Originally intended as a document markup language not a
database language
The ability to specify new tags, and to create nested tag structures
made XML a great way to exchange data, not just documents
XML has become the basis for all new generation data interchange
formats.
A wide variety of tools is available for parsing, browsing and
querying XML documents/data
©Silberschatz, Korth and Sudarshan1.33atabase System Concepts - 5th
Edition, May 23, 2005
Figure 1.4Figure 1.4
©Silberschatz, Korth and Sudarshan1.34atabase System Concepts - 5th
Edition, May 23, 2005
Figure 1.7Figure 1.7

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DDL DML sysytems

  • 1. Database System Concepts, 5th Ed. ©Silberschatz, Korth and Sudarshan See www.db-book.com for conditions on re-use Chapter 1: IntroductionChapter 1: Introduction
  • 2. ©Silberschatz, Korth and Sudarshan1.2atabase System Concepts - 5th Edition, May 23, 2005 Chapter 1: IntroductionChapter 1: Introduction Purpose of Database Systems Database Languages Relational Databases Database Design Data Models Database Internals Database Users and Administrators Overall Structure History of Database Systems
  • 3. ©Silberschatz, Korth and Sudarshan1.3atabase System Concepts - 5th Edition, May 23, 2005 Database Management SystemDatabase Management System (DBMS)(DBMS) DBMS contains information about a particular enterprise Collection of interrelated data Set of programs to access the data An environment that is both convenient and efficient to use Database Applications: Banking: all transactions Airlines: reservations, schedules Universities: registration, grades Sales: customers, products, purchases Online retailers: order tracking, customized recommendations Manufacturing: production, inventory, orders, supply chain Human resources: employee records, salaries, tax deductions Databases touch all aspects of our lives
  • 4. ©Silberschatz, Korth and Sudarshan1.4atabase System Concepts - 5th Edition, May 23, 2005 Purpose of Database SystemsPurpose of Database Systems In the early days, database applications were built directly on top of file systems Drawbacks of using file systems to store data: Data redundancy and inconsistency  Multiple file formats, duplication of information in different files Difficulty in accessing data  Need to write a new program to carry out each new task Data isolation — multiple files and formats Integrity problems  Integrity constraints (e.g. account balance > 0) become “buried” in program code rather than being stated explicitly  Hard to add new constraints or change existing ones
  • 5. ©Silberschatz, Korth and Sudarshan1.5atabase System Concepts - 5th Edition, May 23, 2005 Purpose of Database SystemsPurpose of Database Systems (Cont.)(Cont.) Drawbacks of using file systems (cont.) Atomicity of updates  Failures may leave database in an inconsistent state with partial updates carried out  Example: Transfer of funds from one account to another should either complete or not happen at all Concurrent access by multiple users  Concurrent accessed needed for performance  Uncontrolled concurrent accesses can lead to inconsistencies – Example: Two people reading a balance and updating it at the same time Security problems  Hard to provide user access to some, but not all, data Database systems offer solutions to all the above problems
  • 6. ©Silberschatz, Korth and Sudarshan1.6atabase System Concepts - 5th Edition, May 23, 2005 Levels of AbstractionLevels of Abstraction Physical level: describes how a record (e.g., customer) is stored. Logical level: describes data stored in database, and the relationships among the data. type customer = record customer_id : string; customer_name : string; customer_street : string; customer_city : string; end; View level: application programs hide details of data types. Views can also hide information (such as an employee’s salary) for security purposes.
  • 7. ©Silberschatz, Korth and Sudarshan1.7atabase System Concepts - 5th Edition, May 23, 2005 View of DataView of Data An architecture for a database system
  • 8. ©Silberschatz, Korth and Sudarshan1.8atabase System Concepts - 5th Edition, May 23, 2005 Instances and SchemasInstances and Schemas Similar to types and variables in programming languages Schema – the logical structure of the database Example: The database consists of information about a set of customers and accounts and the relationship between them) Analogous to type information of a variable in a program Physical schema: database design at the physical level Logical schema: database design at the logical level Instance – the actual content of the database at a particular point in time Analogous to the value of a variable Physical Data Independence – the ability to modify the physical schema without changing the logical schema Applications depend on the logical schema In general, the interfaces between the various levels and components should be well defined so that changes in some parts do not seriously influence others.
  • 9. ©Silberschatz, Korth and Sudarshan1.9atabase System Concepts - 5th Edition, May 23, 2005 Data ModelsData Models A collection of tools for describing Data Data relationships Data semantics Data constraints Relational model Entity-Relationship data model (mainly for database design) Object-based data models (Object-oriented and Object-relational) Semistructured data model (XML) Other older models: Network model Hierarchical model
  • 10. ©Silberschatz, Korth and Sudarshan1.10atabase System Concepts - 5th Edition, May 23, 2005 Data Manipulation Language (DML)Data Manipulation Language (DML) Language for accessing and manipulating the data organized by the appropriate data model DML also known as query language Two classes of languages Procedural – user specifies what data is required and how to get those data Declarative (nonprocedural) – user specifies what data is required without specifying how to get those data SQL is the most widely used query language
  • 11. ©Silberschatz, Korth and Sudarshan1.11atabase System Concepts - 5th Edition, May 23, 2005 Data Definition Language (DDL)Data Definition Language (DDL) Specification notation for defining the database schema Example: create table account ( account_number char(10), branch_name char(10), balance integer) DDL compiler generates a set of tables stored in a data dictionary Data dictionary contains metadata (i.e., data about data) Database schema Data storage and definition language  Specifies the storage structure and access methods used Integrity constraints  Domain constraints  Referential integrity (e.g. branch_name must correspond to a valid branch in the branch table) Authorization
  • 12. ©Silberschatz, Korth and Sudarshan1.12atabase System Concepts - 5th Edition, May 23, 2005 Relational ModelRelational Model Example of tabular data in the relational model Attributes
  • 13. ©Silberschatz, Korth and Sudarshan1.13atabase System Concepts - 5th Edition, May 23, 2005 A Sample Relational DatabaseA Sample Relational Database
  • 14. ©Silberschatz, Korth and Sudarshan1.14atabase System Concepts - 5th Edition, May 23, 2005 SQLSQL SQL: widely used non-procedural language Example: Find the name of the customer with customer-id 192-83-7465 select customer.customer_name from customer where customer.customer_id = ‘192-83-7465’ Example: Find the balances of all accounts held by the customer with customer-id 192-83-7465 select account.balance from depositor, account where depositor.customer_id = ‘192-83-7465’ and depositor.account_number = account.account_number Application programs generally access databases through one of Language extensions to allow embedded SQL Application program interface (e.g., ODBC/JDBC) which allow SQL queries to be sent to a database
  • 15. ©Silberschatz, Korth and Sudarshan1.15atabase System Concepts - 5th Edition, May 23, 2005 Database DesignDatabase Design The process of designing the general structure of the database: Logical Design – Deciding on the database schema. Database design requires that we find a “good” collection of relation schemas. Business decision – What attributes should we record in the database? Computer Science decision – What relation schemas should we have and how should the attributes be distributed among the various relation schemas? Physical Design – Deciding on the physical layout of the database
  • 16. ©Silberschatz, Korth and Sudarshan1.16atabase System Concepts - 5th Edition, May 23, 2005 The Entity-Relationship ModelThe Entity-Relationship Model Models an enterprise as a collection of entities and relationships Entity: a “thing” or “object” in the enterprise that is distinguishable from other objects  Described by a set of attributes Relationship: an association among several entities Represented diagrammatically by an entity-relationship diagram:
  • 17. ©Silberschatz, Korth and Sudarshan1.17atabase System Concepts - 5th Edition, May 23, 2005 Other Data ModelsOther Data Models Object-oriented data model Object-relational data model
  • 18. ©Silberschatz, Korth and Sudarshan1.18atabase System Concepts - 5th Edition, May 23, 2005 Database Application ArchitecturesDatabase Application Architectures (web browser) Old Modern
  • 19. ©Silberschatz, Korth and Sudarshan1.19atabase System Concepts - 5th Edition, May 23, 2005 Database Management SystemDatabase Management System InternalsInternals Storage management Query processing Transaction processing
  • 20. ©Silberschatz, Korth and Sudarshan1.20atabase System Concepts - 5th Edition, May 23, 2005 Storage ManagementStorage Management Storage manager is a program module that provides the interface between the low-level data stored in the database and the application programs and queries submitted to the system. The storage manager is responsible to the following tasks: Interaction with the file manager Efficient storing, retrieving and updating of data Issues: Storage access File organization Indexing and hashing
  • 21. ©Silberschatz, Korth and Sudarshan1.21atabase System Concepts - 5th Edition, May 23, 2005 Query ProcessingQuery Processing 1. Parsing and translation 2. Optimization 3. Evaluation
  • 22. ©Silberschatz, Korth and Sudarshan1.22atabase System Concepts - 5th Edition, May 23, 2005 Query Processing (Cont.)Query Processing (Cont.) Alternative ways of evaluating a given query Equivalent expressions Different algorithms for each operation Cost difference between a good and a bad way of evaluating a query can be enormous Need to estimate the cost of operations Depends critically on statistical information about relations which the database must maintain Need to estimate statistics for intermediate results to compute cost of complex expressions
  • 23. ©Silberschatz, Korth and Sudarshan1.23atabase System Concepts - 5th Edition, May 23, 2005 Transaction ManagementTransaction Management A transaction is a collection of operations that performs a single logical function in a database application Transaction-management component ensures that the database remains in a consistent (correct) state despite system failures (e.g., power failures and operating system crashes) and transaction failures. Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database.
  • 24. ©Silberschatz, Korth and Sudarshan1.24atabase System Concepts - 5th Edition, May 23, 2005 Overall System StructureOverall System Structure
  • 25. ©Silberschatz, Korth and Sudarshan1.25atabase System Concepts - 5th Edition, May 23, 2005 History of Database SystemsHistory of Database Systems 1950s and early 1960s: Data processing using magnetic tapes for storage  Tapes provide only sequential access Punched cards for input Late 1960s and 1970s: Hard disks allow direct access to data Network and hierarchical data models in widespread use Ted Codd defines the relational data model  Would win the ACM Turing Award for this work  IBM Research begins System R prototype  UC Berkeley begins Ingres prototype High-performance (for the era) transaction processing
  • 26. ©Silberschatz, Korth and Sudarshan1.26atabase System Concepts - 5th Edition, May 23, 2005 History (cont.)History (cont.) 1980s: Research relational prototypes evolve into commercial systems  SQL becomes industry standard Parallel and distributed database systems Object-oriented database systems 1990s: Large decision support and data-mining applications Large multi-terabyte data warehouses Emergence of Web commerce 2000s: XML and XQuery standards Automated database administration Increasing use of highly parallel database systems Web-scale distributed data storage systems
  • 27. Database System Concepts, 5th Ed. ©Silberschatz, Korth and Sudarshan See www.db-book.com for conditions on re-use End of Chapter 1End of Chapter 1
  • 28. ©Silberschatz, Korth and Sudarshan1.28atabase System Concepts - 5th Edition, May 23, 2005 Database UsersDatabase Users Users are differentiated by the way they expect to interact with the system Application programmers – interact with system through DML calls Sophisticated users – form requests in a database query language Specialized users – write specialized database applications that do not fit into the traditional data processing framework Naï ve users – invoke one of the permanent application programs that have been written previously Examples, people accessing database over the web, bank tellers, clerical staff
  • 29. ©Silberschatz, Korth and Sudarshan1.29atabase System Concepts - 5th Edition, May 23, 2005 Database AdministratorDatabase Administrator Coordinates all the activities of the database system has a good understanding of the enterprise’s information resources and needs. Database administrator's duties include: Storage structure and access method definition Schema and physical organization modification Granting users authority to access the database Backing up data Monitoring performance and responding to changes  Database tuning
  • 30. ©Silberschatz, Korth and Sudarshan1.30atabase System Concepts - 5th Edition, May 23, 2005 Database ArchitectureDatabase Architecture The architecture of a database systems is greatly influenced by the underlying computer system on which the database is running: Centralized Client-server Parallel (multiple processors and disks) Distributed
  • 31. ©Silberschatz, Korth and Sudarshan1.31atabase System Concepts - 5th Edition, May 23, 2005 Object-Relational Data ModelsObject-Relational Data Models Extend the relational data model by including object orientation and constructs to deal with added data types. Allow attributes of tuples to have complex types, including non-atomic values such as nested relations. Preserve relational foundations, in particular the declarative access to data, while extending modeling power. Provide upward compatibility with existing relational languages.
  • 32. ©Silberschatz, Korth and Sudarshan1.32atabase System Concepts - 5th Edition, May 23, 2005 XML: Extensible Markup LanguageXML: Extensible Markup Language Defined by the WWW Consortium (W3C) Originally intended as a document markup language not a database language The ability to specify new tags, and to create nested tag structures made XML a great way to exchange data, not just documents XML has become the basis for all new generation data interchange formats. A wide variety of tools is available for parsing, browsing and querying XML documents/data
  • 33. ©Silberschatz, Korth and Sudarshan1.33atabase System Concepts - 5th Edition, May 23, 2005 Figure 1.4Figure 1.4
  • 34. ©Silberschatz, Korth and Sudarshan1.34atabase System Concepts - 5th Edition, May 23, 2005 Figure 1.7Figure 1.7