What is MongoDB? Introduction and History

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Arpita Gaikwad

University: Sri Balaji University, Pune

School: School of Computer Studies

Course: BCA (Bachelor of Computer Applications)

Interests: NoSQL, MongoDB, and related technologies

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What is MongoDB?

MongoDB is a popular open-source, document-oriented NoSQL database that is used for storing large amounts of unstructured or semi-structured data. Unlike traditional SQL databases that use tables and rows, MongoDB uses documents and collections, making it highly flexible and scalable.

The documents are stored in BSON format (Binary JSON), which allows support for complex data types like arrays and nested objects. MongoDB is known for its high performance, horizontal scalability, and ability to handle real-time data processing needs in modern applications.

History of MongoDB

MongoDB was created in 2007 by a company named 10gen, initially intended to be part of a cloud computing platform. As developers began showing more interest in the database component, the company pivoted to focus solely on MongoDB.

It became open-source in 2009 and quickly gained traction in the developer community. In 2013, 10gen rebranded itself as MongoDB Inc.. The company went public in 2017 on NASDAQ under the ticker symbol MDB, and MongoDB is now one of the most widely used NoSQL databases in the world.

MongoDB Architecture

MongoDB’s architecture is designed to provide scalability, high availability, and performance across distributed systems. It can run on a single server or be scaled to thousands of machines in a cloud-based environment.

• Documents: These are the basic units of data in MongoDB, similar to JSON objects. A document can represent a real-world object and store multiple key-value pairs, arrays, or even embedded documents.
• Collections: A collection is a group of MongoDB documents, similar to a table in SQL. Collections do not enforce a schema, allowing documents within the same collection to have different fields.
• Replica Sets: Replica sets provide redundancy and high availability. They consist of a primary node and one or more secondary nodes that replicate data from the primary. If the primary fails, a secondary is automatically promoted.
• Sharding: Sharding is MongoDB's method of horizontal scaling. It splits large datasets across multiple servers or shards, ensuring better load distribution and query performance.
• mongod: This is the core server process of MongoDB that handles data requests, manages access, and performs background management operations.
• mongos: In a sharded cluster, the mongos acts as a query router that directs operations to the correct shard.

Core Concepts of MongoDB

Understanding the following core concepts is essential to working effectively with MongoDB:

• BSON (Binary JSON): BSON is a binary representation of JSON documents. It allows MongoDB to store more data types, such as dates and binary data, that are not supported in standard JSON.
• CRUD Operations: MongoDB supports standard Create, Read, Update, and Delete operations. These operations can be performed using MongoDB’s query language, which is powerful and flexible.
• Indexing: Indexes help MongoDB locate data efficiently without scanning the entire collection. Types of indexes include single-field, compound, text, hashed, and geospatial indexes.
• Aggregation Framework: The aggregation pipeline allows you to process data records and return computed results. It is used for operations like filtering, grouping, and transforming data — similar to SQL's GROUP BY and JOIN.

Why Choose MongoDB?

MongoDB is highly favored in modern software development for its ease of use, developer-friendly syntax, and ability to handle unstructured data. It’s particularly useful for applications that require high performance and flexible data models.

• Document-Oriented Model: Data is stored in documents that map naturally to application code, making development faster and more intuitive.
• Schema Flexibility: Unlike traditional SQL databases, MongoDB allows each document to have a different structure, making it ideal for agile development and changing requirements.
• Platform Independence: MongoDB runs on all major operating systems and is supported by drivers in many popular languages like Python, Java, Node.js, and C#.
• Built-in Replication and Sharding: These features ensure that MongoDB can provide high availability and scale out easily as the demand grows.

MongoDB vs Relational Databases

Here's a side-by-side comparison between MongoDB and traditional SQL-based databases like MySQL or PostgreSQL:

Feature	MongoDB	Relational DB (MySQL)
Data Model	Document-based (BSON)	Table-based (Rows & Columns)
Schema	Flexible (Schema-less)	Fixed Schema (Pre-defined)
Joins	Limited support via $lookup	Strong support
Scalability	Horizontal (via Sharding)	Vertical (Scale-up hardware)
Transactions	Supported (multi-document in v4.0+)	Fully ACID-compliant

MongoDB vs Other NoSQL Databases

MongoDB is part of the broader NoSQL ecosystem. Here's how it compares with other popular NoSQL databases:

Database	Type	Strengths	Best Use Cases
MongoDB	Document Store	Flexibility, aggregation, rich queries	Web apps, content management, analytics
Cassandra	Wide Column Store	High write throughput, distributed	IoT, logs, time-series data
Redis	In-Memory Key-Value Store	Extremely fast, caching, pub/sub	Caching, real-time analytics
CouchDB	Document Store	Replication, offline sync	Mobile apps, offline-first systems

When to Use MongoDB?

Here’s a quick reference to understand where MongoDB fits best:

Use Case	Why MongoDB is a Good Fit
Content Management System	Schema flexibility helps manage various types of content and formats.
Real-Time Analytics	Aggregation framework is powerful and efficient for processing data in real-time.
E-commerce Platforms	Product catalogs, dynamic pricing, and user carts are easier to model.
Mobile Applications	Offline sync and flexible document storage are ideal for fast-changing mobile data.

MongoDB Today

MongoDB has evolved beyond a simple database into a comprehensive developer data platform. It is used by thousands of companies including Google, Adobe, eBay, and many startups for building high-performance applications.

• MongoDB Atlas: A fully managed cloud version of MongoDB that handles backup, scaling, and monitoring for you.
• Atlas Search: Integrated full-text search powered by Apache Lucene that lets you run complex queries directly on your data.
• MongoDB Realm: A mobile development platform for building offline-first apps with real-time sync capabilities.
• Time Series Collections: MongoDB supports optimized storage and querying of time-based data like sensor logs, financial metrics, and IoT data.

Installing MongoDB

Setting up MongoDB is straightforward. You can install it on Windows, macOS, or Linux. Below are the basic steps for Windows and Ubuntu:

📦 Windows Installation

1. Visit MongoDB Community Downloads.
2. Select your OS and download the MSI installer.
3. Run the installer with default settings (include MongoDB Compass for GUI).
4. Add MongoDB's bin folder to your system PATH for terminal access.

🐧 Ubuntu/Linux Installation

1. Open your terminal and run:

   sudo apt update
   sudo apt install -y mongodb
   sudo systemctl start mongodb
   sudo systemctl enable mongodb
       

2. Check status using: sudo systemctl status mongodb

MongoDB Compass – GUI for MongoDB

MongoDB Compass is the official graphical interface for MongoDB. It allows you to interact with your databases, collections, and documents visually without writing any command-line code.

• View and manage collections and indexes.
• Run queries and aggregations easily.
• Visualize schema structures and performance metrics.

Download it from here. It's beginner-friendly and helps with understanding MongoDB before moving to command line or code.

Basic CRUD Operations

Below are some examples of how to perform CRUD operations using the MongoDB shell (mongosh):

// Create (Insert)
db.students.insertOne({ name: "Arpita", age: 20, course: "BCA" });

// Read
db.students.find({ name: "Arpita" });

// Update
db.students.updateOne({ name: "Arpita" }, { $set: { age: 21 } });

// Delete
db.students.deleteOne({ name: "Arpita" });

These commands allow you to manipulate your data quickly. You can use Compass to visualize these operations too.

Who Uses MongoDB?

MongoDB is trusted by startups and Fortune 500 companies alike. Some notable users include:

• Adobe: For content and digital experience management
• eBay: For storing and analyzing large volumes of user data
• LinkedIn: For internal data services and analytics
• Forbes: For delivering personalized news feeds
• SEGA: For gaming backend infrastructure

Limitations of MongoDB

While MongoDB offers many advantages like flexibility, scalability, and ease of use, it's important to be aware of its limitations. Understanding these helps you choose the right tool for your specific use case.

• Joins are Limited: MongoDB supports joins through the $lookup operator, but it's not as powerful or efficient as joins in SQL databases. For highly relational data, SQL may perform better.
• Memory Consumption: BSON format includes metadata and can consume more memory than plain JSON or relational formats. Indexes also increase RAM usage significantly.
• No Built-in Analytics: Unlike PostgreSQL or specialized analytics databases, MongoDB is not optimized for heavy analytical queries unless combined with external tools like MongoDB Charts or BI connectors.
• Data Duplication: Denormalization (storing related data within documents) can lead to duplication and make data updates more complex.
• Transactions are Limited: MongoDB added multi-document transactions in version 4.0, but they still don't match the full ACID robustness of relational databases like PostgreSQL or Oracle.

That said, these limitations often don't matter for use cases MongoDB is designed for — like real-time applications, content-driven platforms, or fast prototyping.

Key Resources

• Official MongoDB Website
• MongoDB Documentation
• W3Schools MongoDB Tutorial
• MongoDB on GeeksforGeeks

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Written by Arpita Gaikwad | Student at Sri Balaji University, Pune – School of Computer Studies