Introduction To Database

1. What is Data

Data can be defined as a representation of facts, concepts, or instructions in a formalized manner, which should be suitable for communication, interpretation, or processing by human or electronic machine. Data can exist in various forms: as numbers or text recorded on paper, as bits or bytes stored in electronic memory, or as facts living in a person’s mind. All the data are collect in form of binary (1/0) format and transmit from source to destination via internet, wires, signals.

2. What is Database

A database is an organized collection of structured information, or data, typically stored electronically in a computer system. A database is usually controlled by a database management system (DBMS). We can organize data into tables, rows, columns, and index it to make it easier to find relevant information. Basically we use a database for collect data and manage those data in a efficient way thats can be done by a specific software, storage device, and a group of developers to maintain those software and data centers. Many organisation and institute use their own data centre like Google, Facebook, Microsoft etc.

3. What is DBMS (Database Management System)

DBMS (Database Management System) is a software to manage and access the database in efficient way. It basocally manages the data in database. There are various DBMS available like Oracle, Mysql, MsAccess. So DBMS is a package if it is with relational database when it will be called RDBMS(Relational Database Management System)

4. Types of DBMS

Types of databases :

There are many different types of databases. The best database for a specific organization depends on how the organization intends to use the data.

Relational databases :

A relational database is a type of database that stores and provides access to data points that are related to one another. Relational databases are based on the relational model. So DBMS is a package if it is with relational database when it will be called RDBMS(Relational Database Management System).Popular examples of standard relational databases include Microsoft SQL Server, Oracle Database, MySQL and IBM DB2.

Object-oriented databases :

Information in an object-oriented database is represented in the form of objects, as in object-oriented programming. Common examples are Smalltalk is used in GemStone, LISP is used in Gbase, and COP is used in Vbase.

Distributed databases :

A distributed database consists of two or more files located in different sites. The database may be stored on multiple computers, located in the same physical location, or scattered over different networks. some examples of distributed databases include Apache Ignite, Apache Cassandra, Apache HBase, Couchbase Server, Amazon SimpleDB, Clusterpoint, and FoundationDB, CockroachDB etc.

Data warehouses :

A central repository for data, a data warehouse is a type of database specifically designed for fast query and analysis.

NoSQL databases :

A NoSQL, or non relational database, allows unstructured and semistructured data to be stored and manipulated. The most popular databases from SQL and NoSQL are MySQL and MongoDB.

Graph databases :

A graph database stores data in terms of entities and the relationships between entities.

OLTP databases :

An OLTP database is a speedy, analytic database designed for large numbers of transactions performed by multiple users.

Open source databases :

An open source database system is one whose source code is open source; such databases could be SQL or NoSQL databases.

Cloud databases :

A cloud database is a collection of data, either structured or unstructured, that resides on a private, public, or hybrid cloud computing platform. There are two types of cloud database models: traditional and database as a service (DBaaS). With DBaaS, administrative tasks and maintenance are performed by a service provider. The common example of cloud database are Cloud SQL by Google, Azure by Microsoft.

Multimodel database :

Multimodel databases combine different types of database models into a single, integrated back end. This means they can accommodate various data types.

Document/JSON database :

Designed for storing, retrieving, and managing document-oriented information, document databases are a modern way to store data in JSON format rather than rows and columns.

Self-driving databases :

The newest type of database, self-driving databases (also known as autonomous databases) are cloud-based and use machine learning to automate database tuning, security, backups, updates, and other routine management tasks traditionally performed by database administrators. Oracle unveiled the world-first self-driving database as a service that even supports automated performance tuning, self-scaling and self-repairing.

5. What is SQL

SQL stans for structure query language. SQL is a standard language for accessing and manipulating databases. So basically we can manage our data by different operation like insert, delete, display, remove, create etc. All the Relational Database Management Systems (RDMS) like MySQL, MS Access, Oracle, Sybase, Informix, Postgres and SQL Server use SQL as their standard database language.

6. Oracle

Oracle Corporation is the largest software company to develop and markets computer software applications for business. The company is best known for its Oracle database products and, more recently, cloud products and services. Its relational database was the first to support SQL, which has since become the industry standard. Oracle database is one of the most trusted and widely used relational database engines. The biggest rival of Oracle database is Microsoft's SQL Server. Oracle database is a relational database management system. It is also called OracleDB, or simply Oracle. It is produced and marketed by Oracle Corporation. It was created in 1977 by Lawrence Ellison and other engineers. It is one of the most popular relational database engines in the IT market for storing, organizing, and retrieving data.

7. Why Database needed

Absorbing significant increases in data volume :

There are 2.5 quintillion bytes of data created each day at our current pace. Now this amount of data can be increase day by day and it is very challenging factor to manage and store this data, for this reason database is needed.

Ensuring data security:

Every single day we upload and store data in our local system but every system not have it's own data access or security measure and stuffs, so in this condition we have to use a specific database that is maintain user data security.

Managing and maintaining the database and infrastructure:

If we have a large set of data, then we have to manage those data like read and write data, data removing operation etc, so to implement this kind of operation we have to use a unique database system to manage those data in efficient way.

Ensuring data residency, data sovereignty, or latency requirements:

There are lots of chance to have a redundant data in a stored data set. So it is necessary to remove redundant data because it occupy the space in a storage system, in this situation we have to use a specific database for remove redundant data.

8. Advantage of DBMS

Better Data Transferring: Database management creates a place where users have an advantage of more and better-managed data. Thus making it possible for end-users to have a quick look and to respond fast to any changes made in their environment.
Better Data Security: The more accessible and usable the database, the more it is prone to security issues. As the number of users increases, the data transferring or data sharing rate also increases thus increasing the risk of data security.
Better data integration: Due to the Database Management System we have an access to well managed and synchronized form of data thus it makes data handling very easy and gives an integrated view of how a particular organization is working and also helps to keep a track of how one segment of the company affects another segment.
Minimized Data Inconsistency: Data inconsistency occurs between files when different versions of the same data appear in different places.
Faster data Access: The Database management system (DBMS) helps to produce quick answers to database queries thus making data access faster and more accurate. For example, to read or update the data.
Increased end-user productivity: The data which is available with the help of a combination of tools that transform data into useful information, helps end-users to make quick, informative, and better decisions that can make difference between success and failure in the global economy.
Reduction in data Redundancy: When working with a structured database, DBMS provides the feature to prevent the input of duplicate items in the database. for e.g. – If there are two same students in different rows, then one of the duplicate data will be deleted.