Updated June 27, 2023
Introduction to MongoDB Use Cases
MongoDB is used for big data or in other words, we can say that it is the most popular use case for big data storage. MongoDB use cases involve handling large amounts of data. That means if we need fast access to the data, sometimes it is complex to process the traditional data. At that time, we can use MongoDB use cases per our requirements. On the other hand, big data is helping to create new applications as per business requirements. It also helps to improve customer satisfaction.
Different MongoDB Use Cases
Given below are the different use cases of MongoDB:
1. Big Data
One of MongoDB’s most conspicuous conceivable use cases is, as referenced above, Big Data. The term alludes to mass volumes of excessively enormous, quick, and computationally complex information prepared by customary, order-based information handling programming.
Large Data has become an expanding marvel over the previous decade, or somewhere in the vicinity as distributed computing, applications, and online administrations have gotten more universal, close by expanding handling force and capacity. The entirety of this aggregated information has gigantic investigation potential in a wide scope of fields, including finance, meteorology, avionics, online retail, hereditary examination, and segment studies, and that’s only the tip of the iceberg, which is the place where MongoDB comes in.
MongoDB, being a NoSQL database, employs non-relational structures for the following four important points:
- Volume: Alludes to the amount of created and put away information. By and large, volume is the main metric that determines a dataset’s quality, regardless of whether that dataset can be characterized as Big Data.
- Variety: Assortment alludes to the kind structure of the dataset, which can incorporate content, sound, video, pictures, search inquiries, everyday travel courses, and the sky’s the limit from there. A theme can gather information across mediums, providing diverse experiences and filling data gaps that would arise with only a few types of information. This is known as “information combination.”
- Velocity: Speed alludes to the speed at which information is produced and examined, which in Big Data’s case is frequently constant and progressively. For instance, even a 10-second slack following a torrent’s way across interlocking streams and foundation can be deadly if the wave is going at 80kmph. Clearing orders should be generated gradually from enormous volumes of information rather than just 60 seconds before the action is required.
- Veracity: Veracity refers to the nature of the information, such as its production source, level of detail or vagueness, reproducibility, etc. The sheer number of sources in Big Data can cause uncontrollable variations in the quality of singular information, which is why volume, as mentioned above, is often considered the primary quality indicator to determine the most accurate results.
2. Customer Analytics
One of the most important strengths of MongoDB is Big Data analytics. We can scale the analytics as per our requirements. The IoT allows us to increase our business as well as how we can reach customer satisfaction. MongoDB helps us compile and analyze customer interest, and according to customer interest, we provide different choices.
3. Product Data Management
This is another use case of MongoDB, and basically, it is used for the online store and e-commerce solutions. Using the MongoDB component, we can easily manage the product catalog; we can also manage the customer orders; and the store’s inventory and shopping carts.
4. Content Management
This is another use case of MongoDB; using the MongoDB feature, we can store the content we are writing for building a website, particularly considering the images, text, video, etc. MongoDB also allows us to store user comments.
5. Mobile Development and Scaling
The mobile application is dynamic so that we can scale per the market situation.
6. Real-Time Data Integration
Sometimes we need to integrate real-time data with a system of software. So MongoDB provides such a platform to the user, which means that MongoDB provides high efficiency to the complex system.
7. Objective and Data Requirement
Sometimes unwanted output comes, so that we can use MongoDB for that scenario. So as per requirement, we can build the framework like mobile development.
Examples of MongoDB Use Cases
Given below are the examples of MongoDB Use Cases:
Example #1
MongoDB use case for a web application.
By using the MongoDB use case, we can scale the web application. That means sometimes we need to store a large amount of data to easily scale the database as required. MongoDB provides the consistency of data over scalability.
Example #2
It is used to store the Log Events.
When running the web-based application, the web server generates the log message as it generates HTTP requests. That message contains different types of information, such as time, when it is generated, etc. Conversely, when a distributed network is in place, handling log files becomes challenging as they are stored in the same location as the application. So that’s why we can use MongoDB to store these log messages, and it handles like operational intelligence.
- E-commerce applications utilize it.
- Sometimes we need to work with machine-generated data. At that time, MongoDB provided a high volume of data feeds.
- Similarly, we can use it for the stock market and social media.
- For example, eBay, ADHAR, MetLife, etc., these companies used MongoDB.
Conclusion
From the above article, we have seen the basic syntax of the MongoDB use case and different examples of MongoDB use cases. This article showed how and when we use the MongoDB use case.
Recommended Articles
We hope that this EDUCBA information on “MongoDB Use Cases” was beneficial to you. You can view EDUCBA’s recommended articles for more information.
