In this part of the course, we shift the focus from relational databases to NoSQL databases, with a special emphasis on MongoDB. NoSQL is a type of database that does not follow the traditional table-based model with relationships but offers flexibility and scalability in storing large volumes of unstructured or semi-structured data.

What is NoSQL?

NoSQL is a category of database management systems designed to handle distributed and unstructured data. Instead of storing data in rows and columns like in relational databases, NoSQL databases use different storage models such as documents, graphs, key-value pairs, and wide columns. NoSQL is especially useful in situations where data changes constantly or is difficult to structure in a tabular format.

Key Features of NoSQL

• Horizontal Scalability: NoSQL allows adding more servers to handle larger amounts of data without compromising performance.
• Schema Flexibility: Unlike relational databases, NoSQL databases do not require a predefined schema, which makes managing dynamic data easier.
• High Performance: NoSQL is designed to handle large volumes of data and queries at high speed.

Introduction to MongoDB

MongoDB is one of the most popular NoSQL databases in the world. Instead of using tables, MongoDB stores data in JSON format documents (internally BSON), making it an excellent choice for applications handling flexible and unstructured data.

Key Features of MongoDB

• JSON Documents: Data in MongoDB is stored in JSON documents, making it easy to understand and work with, especially in modern web applications.
• Scalability and Replica Sets: MongoDB allows data replication across multiple servers, ensuring data availability and reliability.
• Sharding: MongoDB supports sharding, a technique to divide large data collections into distributed chunks across different servers, improving query performance and scalability.

Installing MongoDB

To start working with MongoDB, we first need to install it on our machine or server. On Linux-based systems, we can install MongoDB with the following commands:

bash

Command Line Interface

MongoDB includes a command-line interface called mongo shell that allows us to interact directly with the database. To open the shell, simply run:

bash

Data Model in MongoDB

In MongoDB, data is stored in collections, which are equivalent to tables in relational databases. Each collection contains multiple documents, which are the equivalent of rows but much more flexible as they can have variable data structures.

Example of a Document in MongoDB

A document in MongoDB is similar to a JSON object. Here is a basic example of how a document might look in the users collection:

json

Key Differences between MongoDB and SQL

• Flexible Schema: Unlike SQL, in MongoDB, we do not need to define the data schema before inserting documents. Each document in a collection can have a different structure.
• JSON-like Queries: Queries in MongoDB are made in JSON format, allowing more intuitive data manipulation.

javascript

Alternatives to MongoDB

While MongoDB is one of the most popular NoSQL databases, there are other alternatives that may be more suitable for certain use cases:

• Cassandra: A distributed NoSQL database, column-oriented, primarily used to handle large volumes of geographically distributed data.
• Redis: An in-memory NoSQL database that acts as a key-value store, ideal for applications requiring low latency.
• CouchDB: A document-oriented database that uses JSON to store data and is known for its replication ability across different nodes.

Summary

In this chapter, we introduced the concept of NoSQL databases, exploring the key differences with relational databases. We also learned about MongoDB, its document model, and how to install and start using this NoSQL database system. In the next chapter, we will delve into data modeling in MongoDB and how to create and manage collections.