MongoDB is a popular document database choice among programmers worldwide. The program can handle unstructured data with ease and brings scalability and flexibility to the querying and indexing processes. Therefore, it is the go-to option for processing big data and designing modern applications. MongoDB projects can give you a peek into all these aspects and also show you how to use this database technology. 

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MongoDB fundamentals

Traditional relational databases store data in columns and rows. In contrast, the MongoDB database program is based on the NoSQL model, where the data objects are stored as separate documents within a collection. Here are the main features of the software:

• Supporting ad hoc queries: MongoDB provides ad-hoc query support by field, range, and regular expressions
• Indexing flexibility: It allows indexing of any field in a document, improving the search speed to a considerable degree
• Assisting replication: It achieves replication using replica sets that host the same datasets, which increases data availability 
• Facilitating file storage: It has the capability of storing large objects or files, making it fit for enterprise document management 
• Allowing server-side execution of JavaScript: It supports the use of Java in querying and aggregation functions, which can also be sent directly to the server for execution
• Creating capped collections: Fixed-size or capped collections in MongoDB drive high performance of the read, create, and delete operations
• Retrieving data from multiple documents: MongoDB uses the JSON query format and dynamic schema for efficient performance

A project-based pedagogy offers the opportunity to experience how these features come into play in real-life applications. Moreover, you can acquire knowledge of the best practices for NoSQL development and also pick up additional systems languages.

MongoDB streamlines data storage. You can access and analyze the data through various clients supported by MongoDB. Its database servers are MongoDB Charts, MongoDB Atlas, and MongoDB Compass. Apart from that, MongoDB also provides flawless compatibility with several operating systems like Windows, Linux, and macOS. Moreover, it is compatible with IDEs like JetBrains (DataGrip), Studio3T, and VS Code. This versatility indicates the usefulness of the $project in MongoDB.

You can set up connections among the MongoDB database and its clients through a preferred programming language. Some of the examples of programming languages supported by MongoDB are C, C++, Java, Go, Python, Node, Scala, Rust, Swift, etc.

MongoDB delivers efficient performance owing to its sharding technique. Sharding means the distribution of data over multiple machines. Furthermore, its scale-out architecture enables you to share data to deal with huge datasets’ fast querying and documentation. The sharding process starts at the collection level when distributing data in a MongoDB cluster. You can apply these concepts in your $project in MongoDB. 

If you are a beginner programmer, it can be tricky to find MongoDB projects that match your learning needs. So, we have listed some reference topics for you below. 

Read: MongoDB Interview Questions and Answers

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Top MongoDB Project Ideas & Topics

1. Content Management System

Clubbing the content assets like text and HTML into a single database helps provide a better user experience. MongoDB has an excellent toolset not only for storing and indexing but also for controlling the structure of a content management system. You can easily design a web-based CMS by using the model proposed by “Metadata and Asset Management” in MongoDB. Additionally, you can use “Storing Comments” to model user comments on blog posts. 

You start working on CMS by mentioning the MongoDB schema design, deploying dependencies, Indexing, and querying. After the schema is designed, you need to create a Node.js application server and the application configuration file. Lastly, you need to add the modules for particular functions you want your CMS to accomplish. These functions are performed using the MongoDB shell, a JavaScript CLI allowing you to interact with MongoDB instances.

Conventional relational database technologies are not quite proficient in CMS. But with MongoDB, you can incorporate all data types as well as metadata when developing robust web applications. You can understand the usefulness of CMS when you work on your MongoDB project.

2. Gaming Project

Data is an essential part of making video games work. Some typical examples of gaming data include player profiles, matchmaking, telemetry, and leaderboards. 

The common thread between all games is that they all have a specific goal. And you have to achieve multiple objectives or pay your way out to reach the end goal. This may involve steps like watering your plants, growing vegetables, serving food in a restaurant, and so on. 

When you are selecting the appropriate database for your application, you need to consider the requirements of the modern gaming environment. Today, video games come in online and multiplayer formats and can reach a massive scale. It is also crucial that they evolve quickly to stay relevant in the fast-paced tech world. In this scenario, MongoDB can solve a lot of problems. It has the capability to add and associate new features to player profiles. It can save multi-level data and can also handle concurrency. 

Video game development utilizes huge data sets. A few prominent examples of data in video games are leaderboards, player profiles, player customizations, and matchmaking. You must consider a database that matches contemporary gaming environments for such reasons.

MongoDB is an excellent database software platform since it can manage online matchmaking on a huge scale. You can discern common issues and determine a solution involving multi-level data when you work on a MongoDB project based on gaming.

3. File Sharing System

You can take up a project to create a system for storing and sharing files, such as Dropbox or Google Drive. Such services are useful for saving and retrieving data without having to load large files into memory. 

For this project, you can write the server on Node.js and save the files in the MongoDB program using GridFS. But before we move further, you should know some basic things about this specification. 

• It can hold files exceeding the size limit of 16MB
• GridFS stores files in two collections, one for file chunks and the other for file metadata
• Upon querying GridFS for a file, the driver reassembles the chunks as required

Now, you can access information from random sections by performing a wide range of queries on these GridFS files. You can even “skip” to the middle of a video or audio file. 

Usually, the application contains a few administrators and will offer access to bigger files that can be shared with particular permissions.

Mongoose GridFS is a MongoDB feature that disintegrates huge data files (exceeding 16 MB) into smaller files. This feature helps you to upload relevant documents to the MongoDB platform. You would install Node modules and develop a Node.js application to develop the web transferring solution. You then need to upload the files in Node.js API and add the Multer package to allow sharing.

You can send the files through emails (using Express Js) or install the project in MongoDB on Heroku for file access. You can expand the script to remove files created before 24 hours from the storage database.

4. Metadata Project

Metadata provides information about other data. Some basic metadata examples include author, date created, date modified, file size, etc. Suppose you hold metadata from a set of images recorded from 100 cameras. Also, each camera gives 100,000 images in a day, and the records are kept for 30 days in each camera. 

Now, consider a web application that fetches all the images clicked in a particular hour. This is how the querying will be performed:

• Selecting a camera
• Selecting a data
• Selecting an hour
• Fetching all images in that hour 

By using the MongoDB database, you can simplify and speed up this entire process. The program would allow you to categorize or aggregate the data into hour-wise, day-wise, or camera-wise collections. You can also easily scale this implementation horizontally. For this reason, designing a metadata schema is one of the most-preferred MongoDB project ideas among students. 

Also learn: CRUD Operations in MongoDB

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5. Logging Application

Servers produce a large number of event logs containing useful information such as errors, warnings, user behavior, etc. Most servers store this data in plain-text log files in their local systems. Plain-text logs are readable and accessible, but this default method is not without its limitations. It is difficult to use, reference, and analyze large event streams without a holistic system. 

MongoDB is a practical storage engine for server log data and other types of machine data. You can store, model, and process reports from raw event data with the Hierarchical Aggregation Method. As for the schema for storing data in MongoDB, the format of your event data will form a significant consideration in your project design.

6. Geospatial Data

Geospatial applications fuse maps and data to produce results via computers. From calculating the shortest distance to your destination to finding out the geographic information of customers, they rely on document databases to a great extent. You can store geospatial data in MongoDB as legacy coordinate pairs of GeoJSON objects. Because of its geo-specific capabilities in storing and indexing, MongoDB is a top choice when it comes to location-oriented services. 

7. Authorization and profiling 

LDAP authorization is one of the most popular MongoDB real world use cases. It is an authentication system wherein users are authorized based on their mapped roles and associated privileges. We have explained the entire mechanism in the example below:

• First, you have to feed images of the concerned persons in the application, store information in the database, and train your model 
• Then, the identification process begins. The app would recognize a person’s face using the camera and display their name (in red color) if their information is stored on the server.
• After this, the information is coss-verified with the MongoDB database. The record searched in the database should match the information shown earlier. And if it does, the person’s name is displayed in green color. 

This project helps develop an authentication system to authorize users depending on their privileges and roles. To build the system, you would store multi-level data, like personal info, identification images, etc., in your MongoDB cluster. Subsequently, you would train your authentication model. 

Make sure to create roles with each one matching an LDAP group ‘Distinguished Name.’ Moreover, the identification process in a project in MongoDB starts when a client connects to MongoDB and undertakes authentication.

Such a system can be used for authenticating people in exclusive events so that there is no need to check invitation cards. A person will be authorized to go inside if the application confirms their details. 

You can extend this project to include the ‘profiling’ functionality for people who are not strongly associated with the system—for example, tracking of criminals, customer rewards, click-through-rates of promotions, etc. In the digital universe, new data and information layers are being added to user profiles every day. MongoDB is a fast program for capturing these connections and evolutions. 

8. Product Catalog

MongoDB is an appropriate solution for maintaining and managing the product catalogs of any business. Generally, a product is composed of some other products, which can change with time and business circumstances. Now, if the base products go on to have more than one brand or identifier, it would be challenging to capture the modifications in other document database types. Due to its flexible schema, MongoDB is used by several e-commerce websites and product data management services. Here are some other significant features of this database software:

This project helps you to create a product catalog management system through the MongoDB Atlas organization. You would develop a schema design activating ‘product search’ on the data stored in open-source analytics, MongoDB Atlas via ElasticSearch and Solr, and search solutions. You can deploy Solr to index documents and install ElasticSearch to activate full-text search in a project MongoDB.

• Using “Inventory Management” to determine patterns and handle interactions between shopping carts and inventory 
• Describing best practices and techniques with the “Category Hierarchy” report 

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9. Billing Solution

The traditional billing and invoicing systems are cumbersome and face the risk of information loss. And a MongoDB-based solution can help you automate and streamline the process, resulting in efficient business operations. But before you begin, there are some important things to consider. 

Every order will contain line items with product data. There can be separate locations for the order’s delivery and billing. Also, orders can progress via many states. You have to keep all these things in mind while putting your document together. With MongoDB, you can handle the concurrency and perform other operations like “add one more.” Additionally, you can keep a tab on all the changes in the bill of sale as it moves through the system. 

Here is a step-wise explanation for building a full-fledged billing dashboard:

• Leverage MongoDB Charts for visualizing the amount within the Atlas Organization
• Invoke the MongoDB atlas API with the Stitch tool to retrieve invoice data
• Insert this data into the MongoDB Atlas cluster to be sourced by the Charts dashboard
• Use Scheduled Stitch Triggers to ensure automatic data retrieval, and hence, keeping the dashboard updated

10. Finance and Investment Applications

The finance industry is full of examples where certain documents contain other documents, which in turn, are composed of more documents. Even investment vehicles are structured in the same manner. Whether it is a bandwidth fund or mutual fund or a fund of funds, your effort is to avoid flattening the data. And to that end, using a document database like MongoDB can prove immensely useful. 

Also read: Hadoop v MongoDB: Which one you should select for Big Data?

11. Fetch and Stream Pricing Data

Try your hand at an application that uses a MongoDB database to store the price updates of the world’s major stock market indices. The primary assumptions are as follows:

• The price data is generated randomly 
• Some arbitrary price data populates the database initially

First and foremost, you would need a working MongoDB setup for storing and retrieving data. You can utilize the cloud service for this purpose. The next step will be to determine the format or schema in which you want to store your data. As for retrieval, MongoDB’s JSON-based querying will enable data from multiple documents.

Once your database server is ready, you will need a server application, perhaps built on Python. This server API will interface with the DB and publish stock data on your broadcast channel. On the front-end, a JavaScript UI will update the display with the latest stock prices.

12. Online Radio Station App

For this project, you can have a look at a widely-used online radio app —for instance, TuneIn. You can access the TuneIn app on the web or your mobile. It lets you listen to music, live news broadcasts, sports, and even podcasts. Now, using these pointers as a reference, make a list of features that you want in your online radio station app. And depending on your selection, decide which programming languages and databases you would use. 

Coming to the development phase, you can build a RESTful (Representational State Transfer) API for the core features and use the MongoDB as the NoSQL document database for API development. 

With the growing industry awareness about the benefits and high-end features of non-relational databases, MongoDB skills have gained a massive demand in the market. Various leading businesses have adopted this system as their backend software—for example, MetLife, eBay, Shutterfly, Aadhar, and many others. Even the top social networks hire skilled database professionals for positions like DB administrator, data architect, systems engineer, etc.

Read : MEAN Stack Developer Salary in India

Advanced MongoDB project ideas:

A challenge is required to keep you learning if you are an expert database administrator or developer. You can use your MongoDB skills to test such advanced projects which can contribute to your portfolio, demonstrate your database administration skills, and assist you to choose additional systems languages. Here are a few advanced MongoDB project ideas you can try:

 1. Work on a Discussion Forum:

You need to practice MongoDB skills like NodeBB, Node.js, and database management to work on this project idea. You must begin creating a discussion forum using MongoDB. Make sure to use the advanced version of MongoDB, Node.js, and Linux. Also, make sure you install, configure, and secure MongoDB before working on a customizable forum.

 2. Develop an open-source chatting app:

You need to practice MongoDB skills like front-end development, back-end development, and database management to work on this project idea. You must consider working on this project if you are a developer experienced with React, Node.js, Socket.IO, and MongoDB skills.

For example, Fiora is a chat application that allows users to store data for prolonged periods. It offers several great features with multiple messaging apps like Telegram and Whatsapp.  In this project MongoDB invites contributions and requests from all developers.

3. Develop a habit-tracking app:

You can use your MongoDB skills like full stack development and database management to develop a habit-tracking app. This app would function like a role-playing game. Generally, open-source platforms have several active projects that allow you to test your skills. This specific test covers an app developed to handle objectives like role-playing games.

4. Develop a workout broadcasting app:

You can apply your MongoDB skills like full stack development and database management. These skills help you to develop an app that allows users to announce their workouts. Exercise and fitness tracking apps are becoming famous among fitness enthusiasts. So, you can develop an application that stores workouts, registers profiles, and broadcasts them online. You can use project MongoDB to store data. But, you may find challenges connecting the application to the existing database.

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Mongodb Real-Time Projects Examples    

MongoDB is a versatile NoSQL database that lends itself well to real-time projects across various domains. Here are some MongoDB real-time project examples to inspire beginners: 

• E-commerce Inventory Management: Build a system to manage product availability and inventory updates in real-time for an online store. 
• Live Analytics Dashboard: Create a dashboard that displays real-time analytics data, such as website traffic, user interactions, and sales metrics. 
• IoT Data Processing: Develop an IoT data processing platform that collects and analyzes sensor data in real-time. 
• Social Media Analytics: Build a tool that tracks and analyzes social media mentions and engagement for brands and influencers. 
• Real-time Chat Application: Create a chat application that allows users to exchange messages and media files in real-time. 
• Location-Based Services: Develop a location-based service that offers real-time information on nearby restaurants, events, or points of interest. 

• Stock Market Tracker: Build a real-time stock market tracking system that provides live updates on stock prices and market trends. 
• Healthcare Monitoring: Create a healthcare platform for real-time monitoring of patients’ vital signs and health data. 
• Online Gaming Leaderboard: Develop a leaderboard for online games that updates scores and rankings in real-time. 
• Live Weather Dashboard: Build a dashboard that displays real-time weather information and forecasts for different locations. 
• Supply Chain Tracking: Create a supply chain tracking system that monitors the movement of goods and inventory in real-time. 
• Smart Home Automation: Develop a real-time smart home automation system that allows users to control devices and appliances remotely. 

These MongoDB real-time projects offer valuable hands-on experience and demonstrate the database’s capabilities in various practical applications. 

Conclusion

The above MongoDB projects combine the theoretical and practical knowledge to help you brush up on the syntax and techniques. So, utilize these resources and learn how to build web solutions with MongoDB!

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