Introduction

We use databases for storing data instead of program's memory. We don't interact with databases directly instead we use a DBMS.

• A database implies that there is a structured way to store and organize data.

There are 2 main category of DBMS

• Relational (SQL based) eg. MYSQL, POSTGRESQL
• NoSQL eg. MongoDB, DynamoDB

NoSQL means that the database does not employ tables, rows and columns for data organization. When we specify what kind of database MongoDB has, we can classify it as NoSQL because it does not employ related tables of data to store information, and it instead uses documents.

A collection of related pieces of data, whose purpose is to solve the data management needs of an institution is called a Database.

Database Management Systems (DBMS) are very complex software which save the data on the secondary storage devices and which are used to manipulate databases.

We use a DB driver to interact with DB from our program, using any other db shell method like mongo shell or SQL.

MongoDB

MongoDB is a no SQL database more specifically a Document based database.

• Document based: MongoDB stores data in documents (field-value pair data structures, NoSQL);
• Scalable: Very easy to distribute data across multiple machines as your users and amount of data grows;
• Flexible: No document data schema required, so each document can have different number and type of fields;
• Performant: Embedded data models, indexing, sharding, flexible documents, native duplication, etc.
• Embedding/Denormalizing: Including related data into a single document. This allows for quicker access and easier data models (it’s not always the best solution though).

Document Based Modelling

Document based database have Collections, and each collection have documents and each document have data in form of key-value pair. Collection can be assumed as Table and Document as the row in relational database each document will have a key-value pair where the key can be assumed as columns.