Easy Notes is the new initiative of D2G where we put everything in Layman Language. As name suggests it is made up with the help of individual’s notes, up to the point and consist no further explanations especially designed for Aspirants who have little knowledge about the respective Subject. Very Good to brush up your knowledge.
Today’s Topic: DBMS One Liner
# 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
# 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 dataNeed to write a new program to carry out each new task
>> Data isolation — multiple files and formats
>> Integrity problemsIntegrity 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
>> 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 usersConcurrent 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.
# Levels 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.
# View level: A way to hide:
(a) details of data types and
(b) information (such as an employee’s salary) for security purposes.
# View of Data: An architecture for a database system
# Instances 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)
>> Physical schema: database design atthe physical level
>> Logical schema: database design atthe 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.
# Data Models: A collection of tools for describing
>> 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
# 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
# Data Definition Language (DDL)
>> DDL compiler generates a set of tables stored in a data dictionary
# Data dictionary contains metadata (i.e., data about data)
>> Database schema
>> Integrity constraints