Database Management systems - Reasons for DBMS – DBMS solves these problems
In the early days:
o Database applications built on top of file systems -> Plethora of drawbacks
Data redundancy and inconsistency
o Multiple file formats, duplication in different files
o Redundancy leads to inconsistency (change in one file need to be reflected in all other
files that contain that data)
Difficulty in accessing data
o Need to write a new program to carry out each new task
Data isolation
o Multiple files and formats
Integrity problems
o Integrity constraints (e.g., account balance > 0) become “buried” in program code
rather than being stated explicitly
o Hard to add new constraints or change existing ones
Atomicity of updates
o Example: Transfer of funds from one account to another should either complete or not
happen at all
o Failures may leave data in an inconsistent state with partial updates carried out
Concurrent access by multiple users
o Needed for performance
o Example: Two people, one adding money (e.g., 100) and the other withdrawing
money (e.g., 50 each) at the same time
o Uncontrolled concurrent accesses can lead to inconsistencies
Security problems
o Hard to provide user access to some, but not all, data
DBMS Architecture
Database (DB):
Collection of data with the same structure
Including correlations and relationships
Common purpose, i.e., defined for a particular use
Shared, i.e., used by several users
Applications:
Access to DB for performing queries
Android app, Web application, etc.
Database Management System (DBMS):
Collection of programs over DB
, Define, i.e., specify the data types, structure, constraints
Build & manipulate, i.e., store on disk, retrieve, update
Administrate, e.g., manage access rights
Black box interacting between users/applications and the database
Ultimate goal
Separate data from application!
Provide an interface that the application programmer must follow
Allow system administrator to make modifications without having an impact on the user
o E.g., improve or reconfigure system
Users can change their view of the data without having to worry about how it is stored
Layers
External Layer - I.e.: communication with users
Analysis of user requests (queries)
Access control
Answer presentation
Logical Layer
Optimization of queries
Resolving conflicting accesses, i.e., multiple users want to do something
Guarantees constant availability even in case of failures e.g. back-up DB
Internal Layer
Storing the data
Software for structuring the data
Efficient access methods I.e., keys, indices, etc.
Development Process (i.e., lifecycle) for DBMS
Planning
Develop a preliminary understanding of the business situation and how information systems
might help solve the problem
Step includes:
o Understand current data processing
o Understand general business functions and needs
Analysis
Analyze the business situation thoroughly to determine requirements
and to structure those requirements
Output → Conceptual Schema Planning Analysis
o Corresponds to a detailed, technology independent specification
of the overall organizational data structure
o E.g., Entity-Relationship model that we will discuss in the
following lectures (image on the right)
Design
, Logical: representation of the DB
o Transform the conceptual schema, i.e., outcome of previous step, in terms of the data
management system
Physical: the set of specifications that describe how data are stored in a computer’s secondary
memory by a specific database management system
Implementation
Build database implementation
Populate with data
Install application(s) and test
Complete documentation and training materials
Maintenance
Monitor the operation and usefulness of the system
Repair by fixing errors in database and applications
Enhance by analyzing the database and applications to ensure that evolving
Information requirements are met
Different types
Traditional database management systems
o Text and numerical data
Multimedia database management systems
o Multimedia data (movies, music, etc.)
Spatial database management systems
o Geographic and geometric data
Data Warehouses
For each type there are different systems we can use
Relation Data Model - Defined
An approach to managing data by representing it grouped into relations
Developed by Ted Codd in 1970 at IBM
Relational DataBase Management Systems, RDBMS:
o A database management system that manages data as a collection of tables in which
all relationships are represented by common values in related tables
Structured Query Language (SQL)
Language for creating & querying relational databases
Simple, expressive, with efficient implementations
Used by many commercial systems:
o Oracle, MySQL, MS Access, SQLite, DB2, Ingres, Sybase, dBase, etc.
Standard for RDBMS:
o Reduced training costs
o Cross-system communication, and more.
, SQL Environment
Catalog: information for included databases
Schema: structure of one database, i.e., tables, views
Data Definition Language (DDL): commands that define a database, including creating,
altering, and dropping tables and establishing constraints
Data Manipulation Language (DML): commands that maintain and query a database
Data Control Language (DCL): commands that control a database, including administering
privileges and committing data
SQL Environment – simplified illustration
Data Definition/Manipulation/Control Language
Basic Concepts
Relational Schema
A1, A2, …, An are attributes
R = (A1, A2, …, An ) is a relation schema
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