Thursday, September 12, 2019

MongoDB Introduction


MongoDB Introduction

Here we are going to learn about MongoDB Introduction part.

SQL essentially used for RDBMS (Relational Database Management System). It uses ACID(Atomic, Consistent, Isolated, Durable) property.



When we are talking about huge data sets that stores data like google (Tera Bytes data every day), which is unstructured and not stored in tabular relations(like relational databases) known as NoSQL.

It stands for Not Only SQL. It is a non-relational database management systems, different from traditional relational database management systems. It is designed to store data at very large scale.
There are four general types (most common categories) of NoSQL databases. Each of these categories has its own specific attributes and limitations. There is not a single solutions which is better than all the others, however there are some databases that are better to solve specific problems. To clarify the NoSQL databases, lets discuss the most common categories :

Key-value: It is most basic types of NoSQL database. It stores data in key-value pair. It can handle huge amounts of data.

Column-oriented: It is mostly worked on columns and it treats every column individually.

Graph: It stores data in graph and is also collection of nodes and edges.

Document oriented: It is a key value collection where key allows access to its value.



MongoDB is free, open-source, cross platform, document oriented database program. It uses JSON-like document with schemas. It is not RDBMS. Any software who stores data in JSON format or in XML format known as document oriented database program.

It stores data in BSON(Binary JSON) format. We can create more than one database in MongoDB.

In MySql, Database is act like a container who keeps tables. In MongoDB, database is container for collection. A Collection is a group of MongoDB documents.

In MongoDB, every documents in a collection should be similar type. Suppose we create a collection named Student. So, it will keep data related to student like, stores name, age, address etc.

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