Data in simple words are characters, quantities or information on which computer performs an operation according to the interpretation. These data are stored in magnetic, optical or mechanical recording media and are transmitted in the form of electrical signals.

Database Management Systems (DBMS) are programs that are developed in order to create and maintain a database, where a database means an organized collection of data. The Database Management Systems are used for the storage, organization, modification, and retrieval of data using a function called Querying. There are various types of the database available, Relational database and NoSQL database are among those.


What is Relational Database?

Relational Database, it is a digital database that is a collective set of data, which is organized in the form of tables that are divided into rows and columns. It was proposed by E. F. Codd in 1970, based on the relational model of data. The software that is used to maintain Relational Database is known as Relational Database Management System (RDBMS).

In Relational Database Management System, the user has to define the tables beforehand, i.e, before the process of data storage starts the user have to define in advance about how many columns and rows are required in the data processing. Therefore, this database can mostly handle structured data.

An important feature of Relational Database is that a single database can be spread out in. A field is specifically designed to maintain the information about the records whereas records are the horizontal entry of individual information in the table.

By using Relational Database, users can customize the way they view the data in the database that is if one user wants to find information from the database on the basis of age and education, whereas other user wants to find information on the basis of address and gender this can be achieved in the Relational Database, thus it allows the users to filter out all the unwanted data leaving them with only the required information.

Most of the Relational Database use Structural Querying Language (SQL). It is a standard querying language that is used to communicate with the data in the database. SQL allows the user to use a series of commands.

These SQL commands are divided into categories, from which the two main are:

Data Manipulation Language (DML) Commands: These commands are used either to extract a particular data, or modify it in order to keep it updated. Some of these commands include, “SELECT” (to query and display data from the database), “INSERT” (to add new rows to the database table),

DELETE” (to delete a specified row or set of rows from the table), “UPDATE” (to bring changes in existing column or a group of the column in the table)

Data Definition Language (DDL) Commands: These commands make changes in the tables or creates tables. Some of these commands include, “DROP TABLE” (to remove all the rows or remove the table definition from the database), “ALTER TABLE” (to add or remove a column from the table).

Another distinguishing feature of Relational Database is that the user can get data from more than one table, this can be achieved only when both the tables have a common column in order to relate them with each other and this feature is known as Join. This common column that relates both the tables is called primary key in the first table whereas foreign key in the second table.



  • Relational Database can be accessed by more than one user, increasing the convenience of using the database.
  • The data are available in clear and concise manner, which allows the user to extract the information easily due to the table format.
  • There is a great level of confidentiality and security with Relational Database.
  • As Relational Database uses SQL, a range of different and complicated commands are able to be carried out on the database.


    • It is complicated to implement and people who are going to implement it, need to have a good experience
    • It is hard to process due to the complexity of the information and data input, it also depends highly on the connectivity and computer speed.


    What is NoSQL?

    NoSQL Database, a digital database that provides a mechanism which does not use the traditional model of tables for the storage and extraction of data. It stands for ‘Not Only SQL’ (Structural Query Language), which means it is possible to use SQL in certain cases in the database but it is not common. NoSQL includes a wide range of technologies, data architectures, and priorities; it represents a school of thoughts. The term NoSQL was first used by Carlo Strozzi in 1998.

    BIG DATA is a set of extremely large and complex data, i.e, analyzed to reveal patterns, trends and associations, especially related to human behaviors and interactions. Big data are difficult to handle and cannot be managed by traditional applications.

    One of the most important feature of NoSQL is that they are built for better handling of Big Data and real-time web apps, thus making NoSQL of great value to the consumers as they have to deal with a large amount of data. The main objectives of NoSQL are to provide scalability, high performance, and high availability.

    NoSQL Database doesn’t require a predefined schema, thus making the insertion of data easy and also any significant changes in the real-time applications can be done without any service interruption. This means faster development, more reliable code integration and less time required for a database administrator.

    This database is auto-sharding friendly that means data is natively and automatically spread across an arbitrary number of servers and the application is not required to be aware of the composition of the server pool. Query load and data are automatically balanced across servers and if a server goes down, it can be quickly and transparently replaced without any application interruption. It also supports automatic database replication to maintain availability and also more sophisticated NoSQL database offer full self-healing, automated failover, and recovery as well as it is able to distribute the database across multiple geographical regions to withstand regional failures.

    Many NoSQL databases have an excellent integrated caching facilities with the help of which frequently used data is kept in the memory of the system, thus removing the requirement of a separate caching layer.

    Let’s look at some of the types of NoSQL Database:

    DOCUMENT DATABASES: In this type of database, each key is paired with a complex data structure known as the documents and this document consist of key-value pairs or key-array pairs. (Ex: CouchDB)

    GRAPHS STORE DATABASES: This database is suited to store data for an application that requires social networking. (Ex: Neo4J)

    KEY VALUE STORES: This is the simplest form of a database, in which all the items in the database is stored as an attribute name or key together with its value. (Ex: Oracle BDB)


      • Easy to use and flexible, object-oriented programming.
      • Uses geographically distributed scale-out architecture.
      • Can handle a large volume of rapidly changing structured, semi-structured and unstructured data.

        Relational Database Vs NoSQL Database

          Relational Database NoSQL Database





        One type of Database (SQL Database).


        Many different types including

        Documents database etc.



        Data is stored in the form of tables which is separated into columns and rows, with each column storing a specific detail about the record. Data is not stored in the form of tables and the model in which data is stored varies based on the database type.




        The table structure has to be defined in advance before the processing of the data. If any alteration is required then the entire database has to be altered, during which the database must be taken offline. No requirement of a predefined schema. New data can be added to the database without any services interruption and also dissimilar data can be stored together.





        This database uses Scale-Up, also known as vertical scaling which means in order to add more data in the server one have to make it powerful by adding external hardware like CPU etc, which can be expensive. This database uses Scale-Out, also known as horizontal scaling which means in order to increase capacity, administrator can just add more commodity servers or cloud instances and the database automatically spreads data across the server. Thus, making the data handling process cheaper.
        DEVELOPMENT MODEL Mixture of both Open-source as well as Close-source Only Open- source
        DATA MANIPULATION Specific language using Select, Delete etc statements Object-oriented APIs




        Configured to strong consistency.

        Depends on products, some provides strong consistency whereas other provides eventual consistency.
        EXAMPLES Oracle Database, Microsoft SQL Database etc. MongoDB,Neo4j etc.

        Full-Forms: ACID – Atomicity, Consistency, Isolation, Durability, APIs – Application Programming Interface



        Relational Database and NoSQL Database, both the database are good at the job for which each one of them is developed that is for storage, organization, and retrieval of data. These databases make the process of storage and retrieval smooth and optimized. But deciding which technology is better can be a difficult task as both of them have their own share of pros and cons. So it depends on the developer to decide which one of them is appropriate for the use according to the requirements and the data to be handled.


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