Databases Lecture Summary

,Lecture I :
introduction



A database CDB) is a collection of data with :




-


a certain logical structure


specific semantics
'


a



specific
-


a users
group of




A database ( DBMS)
management system allows to :




create modify and manipulate database
-



. a



coetrieve) the data using language
'




greenery a
query

support persistent large of data
-




storage of amounts

-


enable durability and
recovery from failure
-



control access to the data
by many users in parallel

without unexpected interactions ( isolation)
'




among users


actions partial ( atomicity)
'



on the data should never be




Motivation for Database Management systems

why not store data in files ?

no
language
-




greenery
Ceimiled directories )
'



weak logical structure to


no efficient access
-




file
searching through large hours
'


a can take


no limited protection
-


or from data loss


no parallel manipulation data
-


access control for of




ANSI SPARC Architecture

Motivation for DBMS :




data independence
'




logical view the data independent physical storage
-


on of

-

user interacts with a simple view on the data


( invisible Ofer )
behind the the
storage structures
'



scenes to are complex

that allow rapid access and manipulation

avoidance duplication
-



of


different views on the same database
-




different users lappli cations
'



for

hiding parts the data for privacy or
security
-




of

This is achieved by the ANSI SPARC Architecture

,ANSI SPARC Architecture : 3 levees


-



different applications might use different
views

data stored physical ( good for
'


once at level


consistency)




view level :




application hide details
-




programs of data types

information
'


hide for privacy or
security
( conceptual schema)
Logical
:
level


describes data stored in database
'


the ,




describes relations data
-




among

Physical level :




how the data is stored
-




disk index record order
'



pages , structures , byte layout ,




This ensures and physical data independence
logical


Data independence

Logical data independence is the ability to modify the
logical schema without


breaking existing applications

applications views
logical database
'

access the , not the




Physical data independence is the ability to modify the physical schema


without
changing the logical schema


workload might cook need
e
change in the for
a :
-




g
- .




different indexing structures
'




different database
engine
'




distributing the database on multiple machines
"




Relational Model


in this course , we work with relational databases


view and level relations
logical represent data as 1 tables


in the pure relational model ,
a table is a



set of tuples :




crows)
'



has no duplicate tuples
-


no order on the tuples

, Relational Model :
schema


Database schema =
structure of the database .
: relations + constraints

)
'



Database instance content C database
'
=
actual State of the at some moment

/




Structured
Query Language
Motivation for database
management systems :




high level declarative
-




query languages
'




greenery tells what you want , independent of storage structure


efficient ( automatic optimisation)
'



data access
query



Declarative
greenery languages
:




describe what information is
sought
'




prescribe desired information
-


not now to retrieve the




imperative vs Declarative Languages
( Kowalski )
Algorithm logic +
=
control




imperative earrgeeages
:
Declarative ecerrgeeages :




control implicit
'




explicit control
-




implicit logic explicit
'




logic
-




(
e.g .

logic programming Prolog)
SQL ( Haskell)
functional programming
A declarative data manipulation ( HTML)
markup languages

language .
the user describes conditions

the requested data is required to ceeefill .




More concise imperative languages
:
than


expensive
-




less program development

easier maintenance
-




Database system will optimise the
query
:




decides possible
-


now to execute the fast
greenery as as




users casually) do need think about efficiency
-


not to




Data Models &
Integrity constraints

Motivation for DBMS :




defined constraints
well data models & data
integrity
- -




relational model
-




meta
language for describing
-




data
-




data relationships
-




-



data constraints

SQL can be used for table and constraint definitions