MongoDB is a popular NoSQL (non-relational) document database that is designed to store, manage, and retrieve large volumes of structured, semi-structured, and unstructured data.

It falls under the category of a document-oriented database management system.

Why MongoDB?

There are several reasons why MongoDB is chosen as a database solution for many applications and some of them are mentioned below -

• Flexibility and Dynamic Schema - MongoDB's document-oriented nature allows for flexible and dynamic data models. It does not enforce a fixed schema, allowing you to easily add, modify, or remove fields from documents as needed.
  
  
• Scalability and Performance - MongoDB is designed to handle large-scale data storage and high-traffic applications. It supports horizontal scaling by distributing data across multiple servers through sharding, enabling applications to scale with ease.
  
  
• Use Case Versatility - MongoDB can be used for a wide range of use cases, including content management systems, real-time analytics, social networks, IoT applications, catalog management, and more.

MongoDB Commands

MongoDB provides a command-line interface (CLI) called the MongoDB Shell (mongo) that allows you to interact with the database and execute various commands. Here are some commonly used MongoDB commands:

• use - Switches to the specified database or creates a new database if it doesn't exist.
  
  

• show databases - Lists all the databases available on the MongoDB server.
  
  

• show collections - Lists all the collections in the current database.
  
  

• db.collectionName.find() - Retrieves documents from a collection based on the specified query criteria. The query is written in MongoDB's query language.
  
  

• db.collectionName.insertOne() - Inserts a single document into a collection.
  
  

• db.collectionName.insertMany() - Inserts multiple documents into a collection.
  
  

• db.collectionName.updateOne() - This command updates the single document in a collection that matches the specified filter criteria.
  
  

• db.collectionName.updateMany() - Updates multiple documents in a collection that match the specified filter criteria.
  
  

• db.collectionName.deleteOne() - Deletes a single document from a collection based on the specified filter criteria.
  
  

• db.collectionName.deleteMany() - Deletes multiple documents from a collection that match the specified filter criteria.
  
  

• db.collectionName.aggregate() - Performs aggregation operations on a collection using a pipeline of stages, such as filtering, grouping, sorting, and more.
  
  

• db.collectionName.createIndex() - Creates an index on one or more fields in a collection to improve query performance.
  
  

• db.collectionName.drop() - Deletes an entire collection.

MongoDB Operators

MongoDB provides a rich set of operators that can be used in queries, updates, aggregations, and other operations. These operators allow you to perform various operations and transformations on data.

Logical Operators:

• $and: logical AND.
• $or: logical OR.
• $not: Inverts the effect of a query expression.
• $nor: logical NOR.

How to Connect MongoDB

To connect to MongoDB, you can follow these steps -

• Install MongoDB
• Start MongoDB Serve
• Choose a Connection Method
• Connect to MongoDB

Difference between SQL and NoSQL Databases

Relational databases (RDBMS) and non-relational databases (NoSQL) have significant differences in their data storage and retrieval models.

• Data Structure -

Relational Databases - Use tables with predefined schemas to store data in rows and columns. Each row represents a record, and each column represents a field or attribute of the record.
Non-Relational Databases - Use various data models, such as key-value pairs, documents, column-family, or graphs. The data structure can be flexible and does not require a fixed schema for all records.

• Schema -

Relational Databases - Enforce a fixed schema, meaning all records in a table must have the same set of columns and data types.
Non-Relational Databases - Offer dynamic or flexible schema, allowing different records to have different sets of fields without a fixed structure.

• Scaling -

Relational Databases - Vertical scaling is typical, meaning increasing the server's resources (CPU, RAM) to handle more load. This approach can become expensive and has practical limitations.
Non-Relational Databases - Horizontal scaling is more common, achieved by adding more nodes to distribute the data and workload. This allows NoSQL databases to handle large-scale applications efficiently.