Download Introduction to Database and DBMS

Relational Database M S
• In this course as discussed last week we will
focus on Relational DBMS:
– Give freedom for adding tables and relationships as
needed and altering the database structure;
• In a relational DBMS, data is organized:
– Field: represent an attribute (column)
– Record: a set of field values (rows..tuples)
– Table: a collection of records (relations)
Fields and Records can be compared to columns
and rows of a Table.
Database Model
1. Hierarchical database store information in the form of a tree where the
relationships are one-to-many. Any relationships between pieces of data
need to be set when creating the database. No further changes can be
made after the creation of the database.
2. Network databases allow one to many or many to many relationships.
Many to many relationships occur in the real world, so network databases
may be more appropriate to such situations than hierarchical databases.
Records are classified as owners or members. Relationship also need to be
set when creating network databases.
3. Relational databases put data into independent tables (files). Users can
then link the tables as they wish with many to many relationships. They are
slower than network and hierarchical databases, but they are more flexible.
4. Object-oriented databases are even more flexible than relational
databases. Instead of tables as in the relational model, you have objects
(eg. patients in hospital database) in the object-oriented database model.
Objects are self-contained, meaning that they store data as well as the
instructions for manipulating the data. Work well with Object Programming
language such as C++ and Java.
Example of DBMS
Database Model
System
Vendor
Relational
MS Access
Microsoft
DB2, SQL Server
IBM
Oracle
Oracle Corp
Foxpro
Hierarchic
Network
Object Oriented
IMS
Intel
System 2000
Culinet
IDMS
Sperry
TOTAL
Cincom Systems
Voss
Logic Arts Ltd
db40
db4Objects, Inc
EyeDB
Sysra
Relational Database Systems
• Following a famous paper written by Ted
Codd in 1970’s
• Database system changed significantly
• Codd proposed that database systems
should present the user with a view of data
organized as tables called relations
Relational Database Systems
• Behind the scenes, there might be a
complex data structure that allow rapid
response to a variety of queries. But unlike
the user of earlier database systems, the
user of a relational system would not be
concern with the storage structure.
Queries could be expressed in a very
high-level language, which greatly
increased the efficiency of database
programmers
Relational Database Systems
• Relations are Tables
- Columns are
headed by attributes
which describe the
entries in the column
Eg. A relation named
Accounts recording
Bank Account,
Balance and Type
might look like:
Acc
No
Balance Type
123
100.00
456
2000.00 Check
…
…
Sav
…
Relational Database Systems
• Heading the columns are the attributes
- Account No
- Balance
-Type
Relational Database Systems
• Below the attributes are the Rows or
Tuples
• The table show two tuples of the relation
explicitly, and the dots below them
suggest that there would be many more
tuples.
Relational Database Systems
• Suppose we want to know the balance of
account 456. We could ask this query in
SQL as follows
SELECT account No
FROM Accounts
WHERE accountNo = 456
Relational Database Systems
• Do NOT expect that this example is
enough to make you an expert SQL
programmer, but it should convey the
high-level nature of the SQL “Select-FromWhere” statement
• High Level………English like command or
statement as compared to programming
language in C++ etc.
Relational Database Systems
• In principle, they ask the DBMS to:
1. Examine all the tuples of the Relation
Accounts mentioned in the FROM clause
2. Pick out those tuples that satisfy some
criterion indicated in the WHERE clause and
3. Produce as an answer certain attributes of
those tuples as indicated in the SELECT
clause
In practice, the system must “optimize” the query and
find an efficient way to answer the query, even though
the relations involved in the query may be very large.
Smaller and Smaller Systems
• Originally, DBMS were large, expensive
software running on large computers
• Size was necessary because to store
large amount of data require large
computer system
• To day many gigabytes fit on a single disk
therefore feasible to run a DBMS on a PC
• Trend – computers size Decrease,
Capacity and power increases.
Bigger and Bigger Systems
• On the other hand, a gigabyte isn’t much data.
• Corporate database often occupy hundreds of
gigabyte
• As storage become cheaper people find new
reasons to store greater amount of data
• Database no longer focus on storing simple data
item (integer or short string of characters) – but
can store images, audio and video and many
other kind of data.
Bigger and Bigger Systems
• Handling such large database require
technological advances
eg. Database of modest size are today stored on arrays
of disks which are called secondary storage device.
(compared to main memory which is primary storage)
• The fact that database systems routinely
assume data is too big to fit in main
memory and must be located primarily on
disk at all times
Bigger and Bigger Systems
• Trends that allow database systems to
deal with large amounts of data faster:
- Tertiary Storage:- tertiary storage devices perhaps storing a tera-byte
each.
- require much more time to access a given item
than does a disk
- involve transporting an object, upon which the
desired data item is stored to a reading device
Bigger and Bigger Systems
- Parallel & Distributed Management
- the ability to store enormous volumes of data is
important but it would be of little use if we could not
access large amounts of data quickly
- thus very large databases also require speed
enhancers.
- parallel Computing handle such problem
Client Server and Multi-Tier
Architectures
• Many varieties of modern software use a
client-server architecture, in which a requests
by one process (the client) are sent to another
process (the server) for execution;
• Entire DBMS is a server, except for the query
interfaces that interact with the user and send
queries or other commands across to the
server. Eg: relational systems generally use the
SQL language for representing requests from the
client to the server then the database server sends
the answer in the form of a table or relation.
Client-Server and Multi-Tier
Architectures
• Also trend to put more work in the client
especially if there are many simultaneous
database users;
• Two tier (client-server) architecture gives way to
three (or even more) tiers
• DBMS continues to act as a server buts its client
is an Application server which manages
connections to the database, transactions,
authorization and other aspects.
• Application Servers in turn have clients such as
Web servers, which support end-users or other
application.
Multimedia Data
• Information that include a signal or move
of some sort. ie: video, audio, radar etc.
• Larger in size then normal data;
• Select a database for an Account
compared to select a picture that look like
• Forces the DBMS to modify its storage
manager
• Answer to a query us a video clip a
gigabyte long……. Will be split into pieces
Information Integration
• Information becomes more essential so
existing information resources are being
used in many new ways ie. Online order
• Legacy database – old collection data
• Data warehouses – varieties of data
• Data mining – search for interesting and
unusual pattern in data ie. sales
END