Database Management Systems Concepts

Database Management System (DBMS) is a software for storing and retrieving users’ data while considering appropriate security measures. It consists of a group of programs which manipulate the database. The DBMS accepts the request for data from an application and instructs the operating system to provide the specific data. In large systems, a DBMS helps users and other third-party software to store and retrieve data.

DBMS allows users to create their own databases as per their requirement. The term “DBMS” includes the user of the database and other application programs. It provides an interface between the data and the software application.

History of DBMS

Here, are the important landmarks from the history:

• 1960 – Charles Bachman designed first DBMS system
• 1970 – Codd introduced IBM’S Information Management System (IMS)
• 1976- Peter Chen coined and defined the Entity-relationship model also know as the ER model
• 1980 – Relational Model becomes a widely accepted database component
• 1985- Object-oriented DBMS develops.
• 1990s- Incorporation of object-orientation in relational DBMS.
• 1991- Microsoft ships MS access, a personal DBMS and that displaces all other personal DBMS products.
• 1995: First Internet database applications
• 1997: XML applied to database processing. Many vendors begin to integrate XML into DBMS products.

Characteristics of Database Management System

• Provides security and removes redundancy
• Self-describing nature of a database system
• Insulation between programs and data abstraction
• Support of multiple views of the data
• Sharing of data and multiuser transaction processing
• DBMS allows entities and relations among them to form tables.
• It follows the ACID concept ( Atomicity, Consistency, Isolation, and Durability).
• DBMS supports multi-user environment that allows users to access and manipulate data in parallel.

Popular DBMS Software

Here, is the list of some popular DBMS system:

• MySQL
• Microsoft Access
• Oracle
• PostgreSQL
• dBASE
• FoxPro
• SQLite
• IBM DB2
• LibreOffice Base
• MariaDB
• Microsoft SQL Server etc.

Types of DBMS

Four Types of DBMS systems are:

1. Hierarchical DBMS

In a Hierarchical database, model data is organized in a tree-like structure. Data is Stored Hierarchically (top down or bottom up) format. Data is represented using a parent-child relationship. In Hierarchical DBMS parent may have many children, but children have only one parent.

2. Network Model

The network database model allows each child to have multiple parents. It helps you to address the need to model more complex relationships like as the orders/parts many-to-many relationship. In this model, entities are organized in a graph which can be accessed through several paths.

3. Relational model

Relational DBMS is the most widely used DBMS model because it is one of the easiest. This model is based on normalizing data in the rows and columns of the tables. Relational model stored in fixed structures and manipulated using SQL.

4. Object-Oriented Model

In Object-oriented Model data stored in the form of objects. The structure which is called classes which display data within it. It defines a database as a collection of objects which stores both data members values and operations.

Advantages of DBMS

• DBMS offers a variety of techniques to store & retrieve data
• DBMS serves as an efficient handler to balance the needs of multiple applications using the same data
• Uniform administration procedures for data
• Application programmers never exposed to details of data representation and storage.
• A DBMS uses various powerful functions to store and retrieve data efficiently.
• Offers Data Integrity and Security
• The DBMS implies integrity constraints to get a high level of protection against prohibited access to data.
• A DBMS schedules concurrent access to the data in such a manner that only one user can access the same data at a time
• Reduced Application Development Time

Disadvantage of DBMS

DBMS may offer plenty of advantages but, it has certain flaws-

• Cost of Hardware and Software of a DBMS is quite high which increases the budget of your organization.
• Most database management systems are often complex systems, so the training for users to use the DBMS is required.
• In some organizations, all data is integrated into a single database which can be damaged because of electric failure or database is corrupted on the storage media
• Use of the same program at a time by many users sometimes lead to the loss of some data.
• DBMS can’t perform sophisticated calculations

When not to use a DBMS system?

Although, DBMS system is useful. It is still not suited for specific task mentioned below:

Not recommended when you do not have the budget or the expertise to operate a DBMS. In such cases, Excel/CSV/Flat Files could do just fine.

DBMS Architecture

The design of a DBMS depends on its architecture. It can be centralized or decentralized or hierarchical. The architecture of a DBMS can be seen as either single tier or multi-tier. An n-tier architecture divides the whole system into related but independent n modules, which can be independently modified, altered, changed, or replaced.

In 1-tier architecture, the DBMS is the only entity where the user directly sits on the DBMS and uses it. Any changes done here will directly be done on the DBMS itself. It does not provide handy tools for end-users. Database designers and programmers normally prefer to use single-tier architecture.

If the architecture of DBMS is 2-tier, then it must have an application through which the DBMS can be accessed. Programmers use 2-tier architecture where they access the DBMS by means of an application. Here the application tier is entirely independent of the database in terms of operation, design, and programming.

3-tier Architecture

A 3-tier architecture separates its tiers from each other based on the complexity of the users and how they use the data present in the database. It is the most widely used architecture to design a DBMS.

• Database (Data) Tier− At this tier, the database resides along with its query processing languages. We also have the relations that define the data and their constraints at this level.
• Application (Middle) Tier− At this tier reside the application server and the programs that access the database. For a user, this application tier presents an abstracted view of the database. End-users are unaware of any existence of the database beyond the application. At the other end, the database tier is not aware of any other user beyond the application tier. Hence, the application layer sits in the middle and acts as a mediator between the end-user and the database.
• User (Presentation) Tier− End-users operate on this tier and they know nothing about any existence of the database beyond this layer. At this layer, multiple views of the database can be provided by the application. All views are generated by applications that reside in the application tier.

Multiple-tier database architecture is highly modifiable, as almost all its components are independent and can be changed independently.

Database Schema

A database schema is the skeleton structure that represents the logical view of the entire database. It defines how the data is organized and how the relations among them are associated. It formulates all the constraints that are to be applied on the data.

A database schema defines its entities and the relationship among them. It contains a descriptive detail of the database, which can be depicted by means of schema diagrams. It’s the database designers who design the schema to help programmers understand the database and make it useful.

A database schema can be divided broadly into two categories −

• Physical Database Schema− This schema pertains to the actual storage of data and its form of storage like files, indices, etc. It defines how the data will be stored in a secondary storage.
• Logical Database Schema− This schema defines all the logical constraints that need to be applied on the data stored. It defines tables, views, and integrity constraints.

Database Instance

It is important that we distinguish these two terms individually. Database schema is the skeleton of database. It is designed when the database doesn’t exist at all. Once the database is operational, it is very difficult to make any changes to it. A database schema does not contain any data or information.

A database instance is a state of operational database with data at any given time. It contains a snapshot of the database. Database instances tend to change with time. A DBMS ensures that its every instance (state) is in a valid state, by diligently following all the validations, constraints, and conditions that the database designers have imposed.

If a database system is not multi-layered, then it becomes difficult to make any changes in the database system. Database systems are designed in multi-layers as we learnt earlier.

Data Independence

A database system normally contains a lot of data in addition to users’ data. For example, it stores data about data, known as metadata, to locate and retrieve data easily. It is rather difficult to modify or update a set of metadata once it is stored in the database. But as a DBMS expands, it needs to change over time to satisfy the requirements of the users. If the entire data is dependent, it would become a tedious and highly complex job.

Metadata itself follows a layered architecture, so that when we change data at one layer, it does not affect the data at another level. This data is independent but mapped to each other.

Logical Data Independence

Logical data is data about database, that is, it stores information about how data is managed inside. For example, a table (relation) stored in the database and all its constraints, applied on that relation.

Logical data independence is a kind of mechanism, which liberalizes itself from actual data stored on the disk. If we do some changes on table format, it should not change the data residing on the disk.

Physical Data Independence

All the schemas are logical, and the actual data is stored in bit format on the disk. Physical data independence is the power to change the physical data without impacting the schema or logical data.

For example, in case we want to change or upgrade the storage system itself − suppose we want to replace hard-disks with SSD − it should not have any impact on the logical data or schemas.