MongoDB - Working and Features
Last Updated :
25 Feb, 2025
MongoDB is a powerful, flexible, and scalable NoSQL database that provides high performance and real-time data processing. Unlike traditional relational databases (RDBMS), MongoDB uses a document-oriented model, allowing developers to store and manage large volumes of unstructured or semi-structured data efficiently.
This article explores how MongoDB works, its core features, and why it is a preferred choice for modern applications.
What is MongoDB?
MongoDB is an open-source document-oriented database that is designed to store a large scale of data and allows us to work with that data efficiently. It is categorized under the NoSQL database because the storage and retrieval of data in the MongoDB are not in the form of tables. MongoDB database is developed and managed by MongoDB. Inc. under SSPL(Server Side Public License) and initially released in February 2009.
It also provides official driver support for all the popular languages like C, C++, C#, and .Net, Go, Java, Node.js, Perl, PHP, Python, Motor, Ruby, Scala, Swift, Mongoid. So, that we can create an application using any of these languages. Nowadays there are so many companies that use MongoDB like Facebook, Nokia, eBay, Adobe, Google, etc. to store their large amount of data.
Working of MongoDB
MongoDB is a database server and the data is stored in these databases. In other words, MongoDB environment gives us a server that we can start and then create multiple databases on it using MongoDB. Because of its NoSQL database, the data is stored in the collections and documents. Hence the database, collection, and documents are related to each other as shown below:
1. Basic Architecture of MongoDB
MongoDB's database structure consists of the following components:
| Component | Equivalent in RDBMS | Description |
|---|
| Database | Database | Stores multiple collections. |
| Collection | Table | Groups related documents. |
| Document | Row | A BSON object containing key-value pairs. |
| Field | Column | Stores data attributes within documents. |
2. Storage Format: BSON (Binary JSON)
MongoDB uses BSON, an extended version of JSON, which supports additional data types like binary data, dates, and nested arrays, improving query efficiency and storage performance.
3. Data Storage and Querying
- Data is stored in collections of documents, making it highly flexible.
- MongoDB supports powerful indexing and real-time queries, ensuring faster read/write operations.
- Developers can store, retrieve, and update data using MongoDB Query Language (MQL), which is similar to JSON queries.
4. Schema Flexibility
MongoDB allows schema-less data storage, meaning:
- Collections can store documents with different structures.
- Fields are not predefined, allowing dynamic updates.
- Suitable for applications where data structures frequently change.
5. Data Relationships in MongoDB
Unlike SQL databases that rely on foreign keys and JOIN operations, MongoDB supports:
- Embedded Documents – Store related data in a single document (reducing the need for joins).
- Reference Documents – Use unique identifiers to establish relationships between documents.
6. Scalability: Horizontal vs. Vertical Scaling
MongoDB is designed for horizontal scaling, meaning it can:
- Distribute data across multiple servers using sharding.
- Support automatic load balancing and replication for high availability.
- Handle big data and distributed workloads efficiently.
For example: we have a database named GeeksforGeeks. Inside this database, we have two collections and in these collections we have two documents. And in these documents we store our data in the form of fields. As shown in the below image:
Features of MongoDB
MongoDB offers a wide range of features that make it a preferred choice for modern applications.
1. Schema-less Database
Unlike traditional relational databases, MongoDB collections:
- Allow different structures within the same collection.
- Do not require fixed column definitions.
- Enable easy updates and modifications.
2. Document Oriented
In MongoDB, all the data stored in the documents instead of tables like in RDBMS. In these documents, the data is stored in fields(key-value pair) instead of rows and columns which make the data much more flexible in comparison to RDBMS. And each document contains its unique object id.
3. Indexing
In MongoDB database, every field in the documents is indexed with primary and secondary indices this makes easier and takes less time to get or search data from the pool of the data. If the data is not indexed, then database search each document with the specified query which takes lots of time and not so efficient.
4. Scalability
MongoDB provides horizontal scalability with the help of sharding. Sharding means to distribute data on multiple servers, here a large amount of data is partitioned into data chunks using the shard key, and these data chunks are evenly distributed across shards that reside across many physical servers. It will also add new machines to a running database.
5. Replication
MongoDB provides high availability and redundancy with the help of replication, it creates multiple copies of the data and sends these copies to a different server so that if one server fails, then the data is retrieved from another server.
6. Aggregation
It allows to perform operations on the grouped data and get a single result or computed result. It is similar to the SQL GROUPBY clause. It provides three different aggregations i.e, aggregation pipeline, map-reduce function, and single-purpose aggregation methods
7. High Performance
The performance of MongoDB is very high and data persistence as compared to another database due to its features like scalability, indexing, replication, etc.
Uses of MongoDB
MongoDB is a popular NoSQL database known for its flexibility, scalability, and performance. It is widely used in various applications across different industries. Here are some common uses of MongoDB:
1. Content Management Systems (CMS):
MongoDB's flexible schema and powerful query capabilities make it an ideal choice for content management systems. It can efficiently handle diverse content types and structures, enabling dynamic and scalable content management solutions.
2. E-commerce Platforms
E-commerce platforms benefit from MongoDB's ability to store and retrieve large amounts of product data quickly. Its flexible schema supports dynamic product catalogs, user profiles, shopping carts, and transaction histories.
3. Real-Time Analytics
MongoDB is well-suited for real-time analytics applications due to its high-performance data ingestion and querying capabilities. It can handle large volumes of data in real-time, making it ideal for monitoring, fraud detection, and personalized recommendations.
4. Internet of Things (IoT)
IoT applications generate vast amounts of data from sensors and devices. MongoDB's scalability and flexible data model allow it to efficiently store and process this data, enabling real-time analysis and decision-making for IoT systems.
6. Gaming Applications
Gaming applications generate complex data structures, such as player profiles, scores, achievements, and game states. MongoDB's document-based model allows for efficient storage and retrieval of this data, supporting high-performance gaming experiences.
7. Log Management and Analysis
Organizations use MongoDB to store and analyze log data from various sources. Its ability to handle large volumes of unstructured data makes it ideal for logging, monitoring, and troubleshooting applications and infrastructure.
9. Customer Relationship Management (CRM)
CRM systems use MongoDB to manage customer data, interactions, and sales pipelines. Its ability to handle complex relationships and unstructured data enables more personalized and effective customer engagement strategies.
10. Social Networks
Social networking applications require a database that can handle complex relationships, user-generated content, and real-time interactions. MongoDB's flexibility and scalability make it an excellent choice for building social networks and community platforms.
11. Big Data Applications
MongoDB is used in big data applications for its ability to store and process large volumes of diverse data types. It integrates well with big data technologies like Hadoop and Spark, enabling advanced data analytics and processing.
12. Healthcare Systems
Healthcare applications use MongoDB to manage patient records, clinical data, and medical images. Its flexible schema allows for the efficient storage of complex healthcare data, supporting better patient care and data analysis.
Advantages of MongoDB
- It is a schema-less NoSQL database. We need not to design the schema of the database when we are working with MongoDB.
- It does not support join operation.
- It provides great flexibility to the fields in the documents.
- It contains heterogeneous data.
- It provides high performance, availability, scalability.
- It supports Geospatial efficiently.
- It is a document oriented database and the data is stored in BSON documents.
- It also supports multiple document ACID transition(string from MongoDB 4.0).
- It does not require any SQL injection.
- It is easily integrated with Big Data Hadoop
Disadvantages of MongoDB
- High Memory Usage - Requires additional storage
- No Complex Joins - Relies on embedding or referencing instead
- Limited Document Size - Maximum 16MB per document
- Nesting Limits - Supports up to 100 levels of nested documents
Difference between MongoDB and RDBMS ?
Some major differences between MongoDB and the RDBMS are as follows:
| MongoDB | RDBMS |
|---|
| It is a non-relational and document-oriented database. | It is a relational database. |
| It is suitable for hierarchical data storage. | It is not suitable for hierarchical data storage. |
| It has a dynamic schema. | It has a predefined schema. |
| It centers around the CAP theorem (Consistency, Availability, and Partition tolerance). | It centers around ACID properties (Atomicity, Consistency, Isolation, and Durability). |
| In terms of performance, it is much faster than RDBMS. | In terms of performance, it is slower than MongoDB. |
Conclusion
MongoDB is a powerful and flexible NoSQL database that caters to the needs of modern applications requiring scalable, high-performance data management. Its schema-less design, horizontal scalability, and rich querying capabilities make it a popular choice for developers and businesses alike. Understanding how MongoDB works and its powerful features can help businesses build high-performance, scalable applications tailored to modern data needs.
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The MongoDB $inc operator is one of the most commonly used update operators in MongoDB, especially when it comes to modifying numerical values within documents. It is used to increment or decrement the value of a field by a specific amount, making it highly useful for applications like counters, sco
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MongoDB - $mul Operator
MongoDB $mul operator is a powerful update operator used to multiply the value of a field by a specified number. This operator allows for direct arithmetic operations within the database, making it particularly useful for scenarios that require modifying numeric field values without needing to retri
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MongoDB - Rename Operator ($rename)
MongoDB $rename operator is a powerful tool for for efficiently renaming fields within documents. This operator ensures data consistency and helps developers maintain a clear and organized schema, especially when working with large collections. Whether you’re dealing with nested documents, arrays, o
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MongoDB - Current Date Operator ($currentDate)
MongoDB provides different types of field update operators to update the values of the fields of the documents and $currentDate operator is one of them. This operator is used to set the value of a field to the current date (either as a timestamp or as a Date). The default type of $currentDate operat
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MongoDB - $setOnInsert Operator
The $setOnInsert operator in MongoDB is a powerful tool used in updating operations with the upsert option. It allows us to specify values that should be set only when a new document is inserted. In this article, we will learn about the $setOnInsert Operator in MongoDB in detail and so on. MongoDB $
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MongoDB Bitwise Update Operator
The MongoDB Bitwise Update Operator allows for efficient manipulation of integer fields within MongoDB documents through bitwise operations. In this article, We will learn about the MongoDB Bitwise Update Operator in detail by understanding various examples in detail.MongoDB Bitwise Update OperatorM
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Array Expression Operators