#1 – What is database?

A database is a collection of data that is organized in a way that allows for efficient storage and retrieval. Databases are used to store and manage data in many different applications, from small personal databases to large enterprise-level systems. They are a critical component of many modern computer systems, and are essential for efficient data management and analysis.

#2 – History of Database

The history of databases dates back to the 1960s, when the first modern computer databases were developed. These early databases were designed to support business operations, and were based on the concept of a hierarchical data model, which organized data into a tree-like structure with a parent-child relationship between the data elements.

Over time, the field of database technology has evolved, and new database models and designs have been developed. For example, the relational model, which was introduced in the 1970s, allowed data to be organized in tables with rows and columns, and allowed for the creation of complex relationships between different data elements. This made it possible to store and manage large amounts of data more efficiently, and paved the way for the development of modern database management systems (DBMS).

Today, databases are an essential part of many different applications, and are used to store and manage data in a wide range of fields, including business, science, and government. The widespread adoption of the internet and the growth of big data have also led to the development of new database technologies, such as NoSQL databases and cloud-based databases, which are designed to handle large amounts of data more efficiently.

#3 – Database Terminologies

Here are some common terms that are used in the field of databases:

• Database: A collection of data that is organized in a specific way, allowing for efficient storage and retrieval.
• Database management system (DBMS): A software program that is used to create, manage, and interact with a database.
• Data model: The structure or organization of data in a database, which defines how data is stored and accessed.
• Table: A collection of data that is organized into rows and columns, similar to a spreadsheet. Tables are a common way to represent data in a relational database.
• Field: A single piece of data within a table, such as a customer’s name or email address.
• Record: A collection of fields that represent a single entity, such as a customer or a product.
• Query: A request to retrieve specific data from a database.
• Index: A data structure that allows for efficient search and retrieval of data within a database.
• Primary key: A field or set of fields that uniquely identifies each record in a table.
• Foreign key: A field or set of fields that refers to the primary key of another table, allowing for the creation of relationships between tables.
• Normalization: The process of organizing data in a database in a way that minimizes redundancy and dependency, and maximizes data integrity.
• SQL: Structured Query Language, a standard language for interacting with databases.
• NoSQL: A class of databases that do not use the traditional relational model, and are designed to handle large amounts of data more efficiently.
• Cloud database: A database that is hosted on a cloud computing platform, allowing for easy scalability and access from anywhere.

#4 – Components of Database

There are several key components of a database, which work together to support the storage and management of data. These components include:

4.1 – Database Software

This is the main program that is used to create, manage, and interact with the database. It includes tools for defining the structure of the database, importing and exporting data, and executing queries and other operations on the data. Examples of database software include MySQL, Oracle, and Microsoft SQL Server.

4.2 – Data Storage

This is the physical location where the data is stored, such as on a hard drive or solid-state drive. The data storage component of a database is typically managed by the database software, and may use a variety of different technologies and formats to store the data.

4.3 – Data Model

This is the structure or organization of data in the database, which defines how the data is stored and accessed. Different data models have different strengths and weaknesses, and are designed to support different types of applications and workloads. Examples of data models include the hierarchical model, the relational model, and the object-oriented model.

4.4 – User Interface

This is the part of the database that allows users to interact with the data, such as through a graphical user interface (GUI) or a command-line interface (CLI). The user interface may provide tools for querying the database, viewing and editing data, and creating reports and other outputs.

4.5 – Query Language

This is the language or syntax that is used to formulate requests for data from the database. Different databases may use different query languages, but many databases support Structured Query Language (SQL), which is a standard language for accessing and manipulating data in relational databases.

4.6 – Indexes

These are data structures that are used to speed up the search and retrieval of data within the database. Indexes are created on specific fields or sets of fields in a table, and allow the database software to quickly locate the records that match a particular search criteria.

4.7 – Security

This is the set of rules and controls that are put in place to protect the data in the database, and to ensure that only authorized users can access the data. Security measures may include authentication, access control, and encryption, and are designed to prevent unauthorized access and data leaks.

#5 – Types of Database

There are several different types of databases, which are designed to support different types of applications and workloads. Some common types of databases include:

5.1 – Relational Databases

These are the most common type of database, and are based on the relational model, which organizes data into tables with rows and columns. Relational databases are well-suited for applications that need to store and manipulate structured data, and support complex queries and data relationships. Examples of relational databases include MySQL, Oracle, and Microsoft SQL Server.

5.2 – NoSQL Databases

These are a class of databases that do not use the traditional relational model, and are designed to handle large amounts of data more efficiently. NoSQL databases are often used in applications that need to store and process unstructured or semi-structured data, such as social media posts or sensor data. Examples of NoSQL databases include MongoDB, Cassandra, and CouchDB.

5.3 – In-memory Databases

These are databases that store data in the main memory (RAM) of a computer, rather than on a disk or other persistent storage. In-memory databases are often used for real-time applications that need to access data quickly, such as online transaction processing (OLTP) systems. Examples of in-memory databases include SAP HANA and Apache Ignite.

5.4 – Distributed Databases

These are databases that are spread across multiple machines or nodes, and are designed to support high availability and scalability. Distributed databases are often used in applications that need to process large amounts of data in parallel, such as data warehouses and big data analytics platforms. Examples of distributed databases include Apache Hadoop and Google Cloud Bigtable.

5.5 – Cloud Databases

These are databases that are hosted on a cloud computing platform, such as Amazon Web Services (AWS) or Microsoft Azure. Cloud databases provide many benefits, such as easy scalability, high availability, and reduced maintenance overhead. Examples of cloud databases include Amazon Aurora and Microsoft Azure SQL Database.

5.6 – Graph Databases

These are databases that are designed to store and query data that is represented as a graph, with nodes, edges, and properties. Graph databases are often used in applications that need to store and process complex, interconnected data, such as social networks or supply chain networks. Examples of graph databases include Neo4j and Apache TinkerPop.

#6 – Role of Database

The role of a database is to store and manage data in a way that allows for efficient access and retrieval. Databases are used in many different applications, and play a critical role in the operation of modern computer systems. Some common roles of databases include:

1. Storing and organizing data: Databases provide a structured way to store data, allowing it to be organized and accessed in a consistent and predictable manner. This makes it possible to store and manage large amounts of data more efficiently, and to retrieve specific data quickly and accurately.
2. Enforcing data integrity: Databases include tools and mechanisms for ensuring the integrity of the data, such as constraints, triggers, and transactions. This helps to prevent data corruption and inconsistencies, and ensures that the data remains accurate and reliable.
3. Supporting data relationships: Databases allow for the creation of relationships between different data elements, allowing for the storage of complex, interconnected data. This makes it possible to represent real-world entities and their relationships, and to query and manipulate the data in meaningful ways.
4. Providing data security: Databases include security features that help to protect the data from unauthorized access, tampering, and loss. This ensures that the data remains confidential and available only to authorized users, and helps to prevent data breaches and other security threats.
5. Enabling data analysis: Databases provide tools and mechanisms for analyzing data, such as SQL query language and indexing. This makes it possible to extract insights and knowledge from the data, and to support data-driven decision making and business processes.
6. Facilitating data sharing: Databases support the sharing of data between different applications and users, allowing for the creation of data-driven systems and ecosystems. This enables collaboration, integration, and interoperability, and helps to drive innovation and productivity.

#7 – Database Functions

A database performs several key functions to support the storage and management of data. Some of the key functions of a database include:

7.1 – Storing Data

The primary function of a database is to store data in a structured and organized manner. This involves creating tables, fields, and records to represent the data, and defining the relationships between different data elements.

7.2 – Indexing Data

A database may create indexes on specific fields or sets of fields in a table, in order to support efficient search and retrieval of data. Indexes allow the database to quickly locate records that match a particular search criteria, and can significantly improve the performance of queries and other operations on the data.

7.3 – Enforcing Constraints

A database may include constraints, which are rules that are used to enforce the integrity of the data. Constraints may be defined at the field level (e.g. a field must not be null) or at the table level (e.g. a record must have a unique primary key), and help to prevent data corruption and inconsistencies.

7.4 – Executing Queries

A database provides tools and mechanisms for executing queries, which are requests to retrieve specific data from the database. Queries may be written in a query language, such as SQL, and may include complex conditions and operations, such as joins and aggregations.

7.5 – Transacting Data

A database supports the use of transactions, which are units of work that are executed atomically, meaning they either succeed or fail as a whole. Transactions help to ensure the consistency and integrity of the data, by allowing multiple operations to be executed together and rolled back if necessary.

7.6 – Providing Security

A database includes security features that are used to protect the data from unauthorized access and tampering. These may include authentication, access control, and encryption, and help to prevent data breaches and other security threats.

7.7 – Backing up data

A database may include tools and mechanisms for backing up data, which involves creating copies of the data and storing them in a safe and secure location. This is important in case of data loss or corruption, and allows the database to be restored to a previous state if necessary.

7.8 – Monitoring and Optimizing Performance

A database may include tools for monitoring and optimizing its performance, such as logs, metrics, and performance counters. This allows the database administrator to identify and troubleshoot any performance issues, and to make adjustments to improve the efficiency and reliability of the database.

#8 – Database or DBMS

Database and DBMS (database management system) are related but distinct concepts. A database is a collection of data that is organized in a specific way, allowing for efficient storage and retrieval. A DBMS, on the other hand, is a software program that is used to create, manage, and interact with a database. In other words, a database is the data itself, while a DBMS is the software that is used to manage the data.

A DBMS provides a variety of functions and features that are designed to support the creation and management of databases. For example, a DBMS may include tools for defining the structure of the database, importing and exporting data, and executing queries and other operations on the data. It may also include features for enforcing data integrity, supporting data relationships, and providing security and backup.

A database is the collection of data that is being managed, while a DBMS is the software that is used to manage the data. The two concepts are closely related, and are typically used together to support the storage and management of data in modern computer systems.

#9 – DBMS

A database management system (DBMS) is a software program that is used to create, manage, and interact with a database. A DBMS provides a variety of functions and features that are designed to support the creation and management of databases, and is an essential component of many modern computer systems.

Some common features and functions of a DBMS include:

• Creating and defining the structure of a database: A DBMS provides tools for defining the structure of a database, including the tables, fields, and relationships between different data elements. This allows the DBMS to store the data in a structured and organized manner, and to enforce data integrity and consistency.
• Importing and exporting data: A DBMS provides mechanisms for importing data from external sources, such as files or other databases, and for exporting data to other applications or formats. This allows for the easy transfer of data between different systems and environments.
• Executing queries: A DBMS includes a query language, such as SQL, that allows users to formulate requests for data from the database. The DBMS parses and executes the query, and returns the results in a structured format.
• Enforcing constraints and rules: A DBMS may include constraints, which are rules that are used to enforce the integrity of the data. Constraints may be defined at the field level (e.g. a field must not be null) or at the table level (e.g. a record must have a unique primary key), and help to prevent data corruption and inconsistencies.
• Supporting transactions: A DBMS supports the use of transactions, which are units of work that are executed atomically, meaning they either succeed or fail as a whole. Transactions help to ensure the consistency and integrity of the data, by allowing multiple operations to be executed together and rolled back if necessary.
• Providing security: A DBMS includes security features that are used to protect the data from unauthorized access and tampering. These may include authentication, access control, and encryption, and help to prevent data breaches and other security threats.
• Monitoring and optimizing performance: A DBMS may include tools for monitoring and optimizing its performance, such as logs, metrics, and performance counters. This allows the database administrator to identify and troubleshoot any performance issues, and to make adjustments to improve the efficiency and reliability of the database.
• Backing up data: A DBMS may include tools and mechanisms for backing up data, which involves creating copies of the data and storing them in a safe and secure location. This is important in case of data loss or corruption, and allows the database to be restored to a previous state if necessary.

#10 – Database Languages

There are several different languages that are used to interact with databases, depending on the type of database and the specific application. Some common database languages include:

10.1 – Structured Query Language (SQL)

SQL is a standard language for accessing and manipulating data in relational databases. It is used to define the structure of a database, to import and export data, and to execute queries and other operations on the data. SQL supports a wide range of operations, including data definition, data manipulation, and data control.

10.2 – NoSQL Query Languages

NoSQL databases, which are a class of databases that do not use the traditional relational model, often use their own proprietary query languages. These languages may be similar to SQL, but may also include unique features and syntax that are specific to the NoSQL database. Examples of NoSQL query languages include MongoDB Query Language (MQL) and Cassandra Query Language (CQL).

10.3 – Procedural Languages

Some databases support procedural languages, which are programming languages that are used to write code that can be executed by the database. These languages may be used to create stored procedures, which are pre-defined units of code that can be executed by the database, or to write custom functions and triggers that can be used to manipulate and control the data in the database. Examples of procedural languages include PL/SQL, T-SQL, and Transact-SQL.

10.4 – Data Definition Languages (DDL)

DDL is a type of language that is used to define the structure and schema of a database. It is typically used to create tables, fields, and other database objects, and to specify the relationships and constraints that are applied to the data. Examples of DDL include CREATE, ALTER, and DROP.

10.5 – Data Manipulation Languages (DML)

DML is a type of language that is used to manipulate the data in a database. It is used to insert, update, and delete data in the database, and to query the data in order to retrieve specific records or aggregate information. Examples of DML include SELECT, INSERT, and UPDATE.

10.6 – Data Control Languages (DCL)

DCL is a type of language that is used to control access to the data in a database. It is used to grant and revoke access to the database, and to manage user accounts and permissions. Examples of DCL include GRANT and REVOKE.

#11 – Database Design and Models

Database design and database modeling are two related but distinct concepts that are used in the development of a database. Database design is the process of planning and defining the structure of a database, including the tables, fields, relationships, and constraints that are applied to the data. Database modeling, on the other hand, is the process of creating a visual representation of the database, using a diagram or other graphical notation.

Database design is an important step in the development of a database, as it defines the structure and organization of the data, and specifies how the data will be stored and accessed. Good database design can help to ensure the efficiency, reliability, and scalability of the database, and can make it easier to maintain and modify the database over time.

Database modeling is often used as a tool to support the design process, by providing a visual representation of the database that can be used to communicate and collaborate with other stakeholders. Database models can be created using diagramming tools, such as the Entity-Relationship (ER) model or the Unified Modeling Language (UML). These diagrams can be used to represent the tables, fields, and relationships in the database, and to document the design decisions and constraints that are applied to the data.

#12 – Database Advantages

Databases have several key advantages that make them an essential component of many modern computer systems. Some of the main advantages of databases include:

12.1 – Efficient storage and retrieval of data

Databases provide a structured and organized way to store data, allowing for efficient access and retrieval. This makes it possible to store and manage large amounts of data more effectively, and to retrieve specific data quickly and accurately.

12.2 – Enforcing data integrity and consistency

Databases include tools and mechanisms for ensuring the integrity and consistency of the data, such as constraints and transactions. This helps to prevent data corruption and inconsistencies, and ensures that the data remains accurate and reliable.

12.3 – Supporting complex data relationships

Databases allow for the creation of relationships between different data elements, allowing for the storage of complex, interconnected data. This makes it possible to represent real-world entities and their relationships, and to query and manipulate the data in meaningful ways.

12.4 – Providing data security

Databases include security features that are used to protect the data from unauthorized access and tampering. This ensures that the data remains confidential and available only to authorized users, and helps to prevent data breaches and other security threats.

12.5 – Facilitating data sharing and integration

Databases support the sharing of data between different applications and users, allowing for the creation of data-driven systems and ecosystems. This enables collaboration, integration, and interoperability, and helps to drive innovation and productivity.

12.6 – Enabling data analysis and decision making

Databases provide tools and mechanisms for analyzing data, such as SQL query language and indexing. This makes it possible to extract insights and knowledge from the data, and to support data-driven decision making and business processes.

12.7 – Offering scalability and flexibility

Databases can be easily scaled up or down, depending on the needs of the application. This allows for the efficient management of data, even as the amount of data grows or the requirements

More to Read

• Relational Database Benefits and Limitations
• Relational Vs Non Relational Database
• Data Warehouse vs Database
• Dataset vs Database
• Database vs DataFrame
• Database Metadata
• 6 Types of Keys in Database
• Postgres Schema vs Database
• Relational Database vs Flat File
• Primary Key vs Foreign Key
• Primary Key vs Candidate Key
• Document Database Vs. Key Value Store
• Document Database Vs. Relational Database
• 13 Examples of Relational Database
• Relational Database Vs. Object-Oriented Database
• 9 Types of Databases
• Distributed Database
• Operational Database
• Personal Database
• Graph Databases
• Document Database
• Centralized Database
• Multidimensional Database

You may have heard the term “centralized database system” and not known what it means.

In a traditional database system, data is stored in multiple files. For example, each customer’s data might be stored in a separate file. In contrast, a centralized database system stores all of the data in one file. This makes it easier to manage the data, and it’s also easier to search the data because it’s all stored in the same place.

With the popularity of computers, it needs to be a system to store data and information from different locations. Numbers of techniques are being used in different computers to store and access information through a network channel. These techniques are known as database management systems which have different protocols to store data and information.

Definition

Centralized database management system is the system in which all the data is stored and managed in a single unit. This is also known as central computer database system. This system is mostly used in an organization, in any Business Company or in institution to centralize the tasks. Data can be accessed through a network Local Area Network (LAN) or Wide Area Network (WAN).  Mainframe computer is the example of centralized database management system.

Functions of centralized database

Distributed query processing

The basic function of centralized database management system is to provide facility and give access to all the connected computers which fulfill all requirements requested by any single node.

Single central unit

All the data and information are stored in single centralized database management system. The computer system which fulfills the requirements of all the connected computers is known as server and other computers are known as clients.

Transparency

All the queries are processed in a single computer system also known as server. There is no duplication or irrelevant data stored in this management system. All connected computer has the access to central computer for their query processing and requirement.

Scalable

No of computers can be added in this centralized database management system. These computers are connected to the system through a network.

What are centralized databases used for?

Centralized databases are often used by organizations to store data that is shared by many users. These are used for storing customer information, inventory data, financial records, and more. They can be used by small businesses or large enterprises. When compared to other databases, they offer a number of benefits over other types of databases.

Centralized database can be accessed by anyone with the proper permissions. This means that multiple people can work on the same data at the same time, which can be a huge time-saver. It also allows for better collaboration, as people can easily share data and ideas reliably. This is because they are hosted on servers that are designed to be up and running all the time. This means that if one server goes down, the others can still be accessed.

Advantage of centralized database system:

Data integrity

Data is more unified as it stored in single computer system and managed. It is easier to communicate and coordinate to get more reliable and meaningful data.

Data redundancy

Data is centralized and stored in one location only. There is no duplication of data and irrelevancy in data.

Data security

Due to storage of data in centralized computer system, the security of data needs to be stronger. Centralized database management system is more secure and more efficient.  

Scalability and localization

New computer systems can be added or removed in centralized database management system more easily.

Data portability

Data can be easily transferred from one computer to another computer because it is stored in centralized database management system.

Lesser cost and maintenance

The centralized database system is cheaper in installation and maintenance than other database management systems and it required single storage system and data can be accessed by all the connected computers.

Disadvantage of centralized database system

Slow processing

In centralized database management system, data is stored in one location and it access and processing speed is lesser than other management system. It requires more time to access the data from one location.

Less efficiency

If the multiple users try to access and process query toward server simultaneously then it creates problem. The processing speed of the central computer turns into low. These problems may reduce the efficiency.

Loss of data

In centralized database management system, if any system failure occurs or any data is lost, then it is not recovered.  

Further Reading

• 9 Types of Databases
• Distributed Database
• Personal Database

In this modern era, numbers of techniques are used to store and manage the data and information. There are a number of database management systems which provides a mechanism to store large amount a data in single or distributed management systems.

Definition

Personal database system is the local database system which is only for one user to store and manage the data and information on their own personal system. There are number of applications are used in local computer to design and managed personal database system.

Functions of personal database

Support one application

Personal database management system requires only one application to store and manage data in personal computer.

Having a few tables

Personal database management system is based on small database consisting of few tables in local or personal computer. It is easily to handle and manage. There is no need to install other devices to access and control the data and information.

Involve one computer

In this database management system only one computer which is involved to store and manage database in personal computer.

Simple design

Design in database management system has much importance for storing and controlling the data. In personal database management system, there is simple design to store data and information.

Advantage of personal database system

Fast processing

Based on the local computer the data can be processed more fast and reliable in terms of handling.

Higher security

Data is stored in personal computer does not need any special security arrangement for authorization of data.

Disadvantage of personal database system:

Fewer amounts of data

Fewer amounts of data and information are stored in personal database management system. There is no connectivity with other computer to get more data.

No connectivity for external database

Personal database management system has only personal database system. There is no connectivity with other computer system or database system to access the data and information.

Further Reading

• 9 Types of Databases
• Distributed Database
• Distributed Database
• Relational Database
• Examples of Relational Database
• Relational Vs. Non-Relational Database

A database is a repository, which effectively stores information, and this stored information can be retrieved by utilizing some particular programming language.

A database is essentially an archive of information, which is formulated so as to help effective information storing. The database is a methodical gathering of information.

Since open library stores books, we could likewise say that a library is a database of books. In any case, entirely characterized, databases are PC structures that spare, compose, secure, and convey information.

Furthermore, a database is constructed and kept up by utilizing a database programming language. The most widely recognized database language is SQL; however, there are different “flavors” of Structured Query Language (SQL).

Each kind of SQL has contrasts in the SQL language structure and are intended to be utilized with a particular sort of database. For instance, an Oracle database deploys the PL/SQL and Oracle SQL, whereas, Microsoft database put to use Transact-Structured Query Language (T-SQL).

Examples

• Every mobile service provider uses a database to store the particulars of their customers.
• An online telephone catalog of any particular city/country would utilize a database to store information regarding people, their addresses, telephone numbers, and other details.

Database Components

A database is comprised of the following primary parts.

Schema

A database contains at least one composition, which is essentially a gathering of at least one table of information.

Table

Each table contains various columns just like in a spreadsheet. A table can have as meager as two columns and upwards of one hundred or more columns, depending upon the kind of information being put in the table.

Column

Each column contains one of a few sorts of information, such as name, address, phone number, etc.

Row

Data in a table is recorded in rows. There are hundreds or thousands of rows in a table having any particular information.

Types of Database

There are several types of databases, some of which are listed here.

1. Distributed Database
2. Centralized Database
3. Personal Database
4. Relational Database
5. Operational Database
6. Hierarchical Database
7. Cloud Database
8. Object Oriented Database
9. NoSQL Database

1. Distributed Database

It is a database that comprises of at least two documents situated in various destinations either on a similar system or on unique systems. Parts of the database are put away in various physical places and handling is disseminated among different database hubs.

Distributed databases are physically stored across multiple locations and logically interconnected with each other and they are usually signifying a solitary logical database.

Distributed databases can be homogenous or heterogeneous. Generally, distributed databases may include the following features:

• Hardware independent
• Location independent
• Operating system independent
• Network independent
• Transaction transparency
• Distributed query processing
• Distributed transaction management

Examples of distributed database:

• Apache Cassandra
• Apache HBase
• Apache Ignite
• Couchbase Server
• Amazon SimpleDB
• FoundationDB
• Clusterpoint

Replicated Data

It is a type of distributed database, which is used to create examples of data in various parts of the database. It can be divided into these two categories.

1. Read only data
2. Writable data

Advantages of Distributed Database:

• Administrators can face lower communication costs for distributed database frameworks if the information is found near where it is utilized the most, whereas, it is not possible in centralized database.
• It is easy to update and growth.
• Increases consistency and ease of use
• Ensures better performance
• Loss of database from one place may not cause loss of all data.
• Effective for load balancing and reduces latency.
• Distributed database has the capability of fault tolerance

Disadvantages of Distributed Database:

• Enforcement of integrity may require more network resources.
• More complexity as its architecture requires better design, administration and troubleshooting.
• Sometimes, problems faced during accessing from the master database.
• Security is another concern in distributed database
• Lack of standard and experience

Read further about Distributed Database and its Types

2. Centralized Database

A centralized database framework is a framework that keeps the information in one single database at one place.

Advantages of Centralized Database:

• Centralized database storage improves data safeguarding. 
• Centralized database provides physical security as locally stored data signifies an ongoing physical security hazard.
• Maintenance of centralized storage is less costly than multiple storage spaces.
• Easy to share ideas across the market analysts.
• It reduces conflicts due to centralization
• Centralized database reduces conflicts amongst organizations and they can focus on their vision and promptly act.
• In centralized database, the data redundancy is negligible.

Disadvantages of Centralized Database:

• Centralized database can be unresponsive to work under a heavy workload.
• Administrators can face high communication costs if the information is not found where it is utilized the most.
• In centralized database, information is stored within a single database so the chance of data loss may increase.
• No proper database recovery measures

Centralized Database and its Functions

3. Personal Database

Information is gathered and stored on PCs, which is in small quantity and can easily manageable.

This information is commonly utilized by the same department of an association and can easily be accessed by a small number of people.

Generally, a personal database system can support one application at a time, involve a single computer, a database having few tables.

Advantages of Personal Database:

• Improve data sharing and security
• Better data integration and fast data access
• Fast end-users productivity and improved decision making

Disadvantages of Personal Database:

• Increased cost due to the requirement of licensing and proper training of database users, and administers to utilize and manage the new traits.
• Personal database can be unresponsive to work under a heavy workload.

Read also: Personal Database Functions

4. Relational Database:

A relational database is described by a set of tables from where data can be accessed.

Relational database can store a large amount of information in a set of tables, which are linked to each other.

Each table is composed of information in rows & columns in which each column represents a particular type of information like name, address, each row contains unique information and each field in a table has its own data type.

Advantages of Relational Database:

• Relational database is used to store the financial record of any company
• It keeps records of customers’ consignments and their orders.
• Relational database ensures data integrity and better performance.
• It provides better data security and allows multiple users.
• A vast amount of data can be stored in relational database, which can easily extendable and modifiable.
• Several clients can access the same database.

Disadvantages of Relational Database:

• High setup and maintenance cost
• Sophisticated networking and hardware setups are required for relational databases.
• Few relational databases have bound on field lengths.

Read also: What is relational database?

5. Operational Database:

An operational database is used to store and manage a huge amount of data in real-time. Data regarding operations (marketing, services provided to customers & relations with them) of any project can be stored inside an operational database.

A national climate administration consistently gathers information from computerized climate stations that produce convenient climate gauges and as an authentic record for scientists.

Similarly, a company permits its sales reps in the field to update sales information in order to boost revenue. Microsoft, Oracle, Amazon Web Services, SAP and IBM are the important players in Operational Database Management System (ODBMS)

Advantages of Operational Database:

• It ensures real-time operations as data can be added and modified in real-time.
• Operational database provides up-to-date information.
• It supplies data for real-time computation and analyzing processes.
• It is helpful to run the day to day operation of the business.

Disadvantages of Operational Database:

• Real-time analysis requires special training sessions for database users which impose more cost on companies.
• Queries against operational data are usually narrow in scope i.e. speed critical.

6. Hierarchical Database:

In hierarchical database model, data is organized in a tree structure that links a number of different elements to one parent record.

Each record type has only one parent. Top element of tree is called parent while its branches are called children. It is useful for certain types of data storage and most popular in the time of mainframe computers.

An entity type is corresponding to a table and entity types are related to each other with one-to-many association.

Advantages of Hierarchical Database:

• Hierarchical databases are easy to comprehend 
• In hierarchical structure clear chain of command
• In hierarchical database, navigating among the records is fast enough as the parent and child relationships are implemented with pointers from one data record to another record.

Disadvantages of Hierarchical Database:

• Hierarchical structures have no tendency to adopt new changes rapidly.
• Communication barriers
• Cannot change the database to ensemble current business’ requirements

7. Cloud Database:

Cloud database is a kind of database administration that is deployed and delivered through a cloud platform like Platform-as-a-Service (PaaS) that permits the organizations and their applications to store and mange information from the cloud.

In present era, it got popularity due to several benefits like acquiring more storage capacity, high bandwidth, scalability and availability as per the payment ability of the user.  

A cloud database regularly functions as a standard database arrangement that usually executed through the installation of database programming over a registering/framework cloud.

In addition, a cloud database is likewise conveyed as an administration, where the merchant specifically deals with the backend procedures of database installation and deployment.

Advantages of Cloud Database:

• Cloud database provides great flexibility to run database workload either traditionally or as a service.
• Helpful for disaster recovery
• Companies can reduce the annual operating costs by utilizing cloud storage
• Easy to access data via internet

Disadvantages of Cloud Database:

• Data protection is a great challenge in cloud database.
• Difficult to access in case of absence of internet connection
• More conscious during drag & drop action to move a document into the cloud storage folder

8. Object Oriented Database

It is a group of object-oriented programming and relational database, which is organized around object rather than actions and logic.

Some examples of object-oriented database engines are Smalltalk, db4o and Cache. Information is described in the form of objects in object-oriented database. Alike objects are categorized to classes and sub-classes and relationship between two objects is maintained by utilizing the notion of opposite reference.

Advantages of Object Oriented Database:

• Permits the integration of databases, operating system, word processors spreadsheets, and other applications
• Ensures the referential sharing of products and applications
• Easily creates a new object from an existing object
• Object Oriented Database Management System permits to create persistent object to solve the issue of concurrency and recovery.

Disadvantages of Object Oriented Database:

• Storage of huge ADTs and structured objects
• Query processing and optimization is a complex task
• It is much more complex that Relational Database, so professional programmers required instead of inexperienced end users.
• User cannot permit access rights on individual objects and classes
• Absence of standard query language to Object Oriented Database as Structured Query Language to Relational Database Management System

9. NoSQL Database:

NoSQL database is used to efficiently manage and analyze a large set of distributed data that might be stored at several virtual servers. Types of NoSQL database are:

• Document Stores
• Key-value data Stores
• Wide Column Stores
• Graph Stores 

Many NoSQL data stores are available now, some of which are, MongoDB, CouchDB, GemFire, Casandra, Hbase, Mnesia, Memcached, and Neo4j

Advantages of NoSQL Database:

• Easy to use and flexible due to Object-oriented programming
• It has geographically distributed scale-out architecture as a substitute of monolithic architecture
• Frequent code pushes and quick schema iteration
• It offers better performance and high global availability
• It also offers flexible data modeling
• Massive volumes are easily handled by NoSQL databases

Disadvantages of NoSQL Database:

• Advance expertise is required for its installation and maintenance.
• Most common business intelligence gadgets do not provide connectivity to NoSQL Databases.