With the rapid evolution of database systems, many companies are now intentional with the Database Service Provider they use. Choosing a suitable database would help improve crucial aspects of your company’s application design. Relational Database Management Systems(RDBMS) like SQL, Oracle, Server, DB2, and PostgreSQL are some of the oldest in the industry. However, NoSQL databases like MongoDB have grown more prominent. There are several MongoDB Use Cases in Real-World. Many companies now adopt MongoDB for their applications.
In this article, you will learn about the Best Real-World MongoDB Use Cases.
Table of Contents
What Is a NoSQL Database?
NoSQL, which means ‘not only SQL,’ is an approach to Database Management that suits several Data Models, including document, columnar, graph formats, and key-value. A NoSQL database is a Data Storage and Retrieval Mechanism modeled in ways other than the traditional table structures utilized in Relational Databases.
NoSQL Databases are compatible with several data models for storing and accessing data. These types of databases have become more famous in the era of Big Data and high volume web, Cloud, and mobile applications, although they have been around for a while now. Most NoSQL databases are scalable across different data centers. They also run as distributed systems, enabling them to perform better with Cloud Computing Infrastructure.
What is MongoDB?
MongoDB is a Distributed Architecture and an Open-source NoSQL Database Management Program with the essential function to create highly accessible and adaptable web-based technologies. MongoDB tool is widespread among database development players because it offers an incredibly flexible schema. In addition, MongoDB, which provides drivers for all scripting languages, enables users to create their app without wasting time setting up a database. It also offers other advantages over traditional RDBMS.
Key Features of MongoDB
MongoDB offers a world of advantages to companies needing a reliable database. Here are some benefits of using MongoDB:
- Speed: MongoDB is 100 times faster than the average Relational Database. As a document-oriented database, MongoDB makes accessing documents easy by indexing. This facilitates quick query response, which saves users valuable time.
- Sharding: Another advantage benefit MongoDB provides is that it allows users to store extensive data. This is done by distributing the data to several servers connected to the application. If one server can’t handle the size of the data, it is shared to another server through a process called auto-sharding.
- Flexible Database: MongoDB allows users have different types of data in a separate document because it is a schema-less database. This affords its users high flexibility and the freedom to store data of any kind.
- Horizontal Scalability: MongoDB is a horizontally scalable database, which is one of its essential advantages. It allows users to distribute large amounts of data to several machines efficiently.
- Transaction Feasibility: Some MongoDB features include gridFS and Replication. These features support an increase in Data Availability while using MongoDB. This ensures that the applications’ performance is very high.
- Absence Of Schemas: MongoDB is NoSQL, meaning it does not require schemas. Therefore, it’s unnecessary to outline your database schemas when using MongoDB. This cuts down the amount of time your database takes to process information. Thus, your schema will be defined by the algorithm you code.
Limitations of MongoDB
As much as MongoDB offers significant advantages over other databases, it is not perfect. It has some limitations that need to be worked on. Here are some of the disadvantages of MongoDB.
- Joins Not Supported: Unlike rational databases that support joins, MongoDB doesn’t. Although joins functionality can be added by coding it manually, it may be slow to execute and affect performance.
- High Memory Usage: MongoDB is designed to store key names for every value pair. It is also affected by data redundancy because it lacks the functionality of joins. This results in high memory usage.
- Limited Data Size: The maximum document size allowed with MongoDB is 16MB. This is a serious challenge that needs to be rectified.
- Limited Nesting: MongoDB offers limited nesting access, as users can’t perform more than 100 levels of nesting of documents.
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- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- Connectors: Hevo supports 100+ Integrations to SaaS platforms such as WordPress, FTP/SFTP, Files, Databases, BI tools, and Native REST API & Webhooks Connectors. It supports various destinations including Google BigQuery, Amazon Redshift, Snowflake, Firebolt, Data Warehouses; Amazon S3 Data Lakes; Databricks, MySQL, SQL Server, TokuDB, MongoDB, DynamoDB, PostgreSQL Databases to name a few.
- Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
What are the Applications of MongoDB?
Various web applications use MongoDB as their primary data store. This is because MongoDB offers high-value storage capabilities. For instance, MEAN is one of the most popular Web Development Stacks that uses MongoDB as the data store. Here are a few essential MongoDB use cases:
1) Content Management
Decades ago, websites could be built with just static text. However, with the constant evolution of the technology industry, creating a website in such a manner will be considered outdated. Today, a website must have videos, audio, an array of text, and social media to catch its user’s attention.
Building quality websites on a Relational Database is challenging. Thankfully, MongoDB provides compatibility and access to such content on a single database. This is because it supports several unstructured and structured data.
2) Internet of Things (IoT)
IoT is one of the most appreciated technological innovations in the world today, connecting billions of devices globally. With IoT, companies improve productivity, redefine their revenue models, and leverage operational efficiency. MongoDB helps to maximize the full potential of IoT devices. Its intelligent Data Platform speeds up the operation and delivery of IoT devices.
3) Real-Time Analytics
With RDBMS Databases, Analytics and Transactional Databases were usually separate. Data from the Transactional Database would have to be moved to the Analytics environment, which required an immense Daily Data Load. With NoSQL databases like MongoDB, companies can now Analyze Data in Real-time while saving costs.
Nowadays, customers prefer to conduct business transactions on their smartphones. As a result, vast numbers of people use mobile applications daily. RDBMS cannot always manage such vast numbers of concurrent transactions. However, MongoDB offers a cost-effective approach to increase customers and app development.
This has led to many financial companies, care providers, and commerce heavyweights deploying MongoDB Smartphone apps for their businesses. The Flexible Data Format and Strong Query Capability of MongoDB allow companies to create great smartphone applications and assist customers in growing their businesses. Companies such as Automatic Data Processing, Inc. (ADP) and The Weather Channel have even expressed their great experiences with this tool for smartphone apps to develop their operations.
Real-World MongoDB Use Cases
Following are the commonly found Real-Word MongoDB Use Cases:
MongoDB Use Case 1: Product Data Management
MongoDB is perfect for Product Data Management. It enables product data and related information to be managed and processed in a single, central system. This allows for Detailed Cost Analysis, Increased Productivity, and Improved Collaboration.
MongoDB Use Case 2: Operational Intelligence
Another real-world MongoDB use case is Operational Intelligence, as it aids in Real-time Decision-making. It allows companies to seamlessly gather various data feeds representing their ongoing business operations and information of related external factors. They can then analyze these feeds as the data arrives for developing profitable and functional business strategies.
MongoDB Use Case 3: Product Catalog
Product catalogs have been in existence for years in the ever-evolving digital space. However, with the rapid evolution in technology, product catalogs sometimes feel like a new digital experience. This is because the richness and volume of data feed product catalogs’ interactions today are remarkable.
MongoDB is useful in such applications, as it provides an excellent tool for storing different types of objects. In addition, its Dynamic Schema Capability ensures that product documents only contain attributes relevant to that product.
MongoDB Use Case 4: Scaling And Application Mobility
For most Mobile Application Development, it is expected that the companies involved will have to deal with different data structures from several sources and potentially highly dynamic growth. Interestingly, MongoDB provides High Flexibility and Scalability that serves as an excellent database solution for such challenges. In addition, it allows developers to focus on developing a better customer experience, instead of spending time adjusting the database.
MongoDB Use Case 5: Customer Analytics
Creating an exceptional customer experience is essential to staying relevant in the market and competing healthily with the competition. This has increased people’s expectations of what a good customer experience should look like over the past few years. Companies are ready to go out of their way to meet and exceed their customers’ expectations.
Data aggregation allows many companies to create exceptional customer experiences. This is because they can collect massive amounts of data of their potential and existing customers, and add it with publicly available data.
With this, they will have clearer insights into how their customers interact with products. It further allows them to make effective strategies on how to satisfy their customers and retain them. MongoDB is perfect for Data Aggregation and Building Analytical Tools for creating exceptional customer experiences.
MongoDB Use Case 6: Mainframe Offloading
Despite the high operational cost and new databases dominating the market, Mainframe remains essential in infrastructure. This is because moving data off the Mainframe is a challenging task. However, MongoDB is efficient in offloading data from mainframe systems at reduced operational cost.
MongoDB Use Case 7: Real-Time Data Integration
Companies usually have huge amounts of data distributed across their organization. These data are valuable when aggregated in a single view. MongoDB provides top-notch flexibility and query capabilities that make aggregating and organizing data more efficient.
Real-life Examples Of MongoDB Use Cases
You have looked at some of the MongoDB use cases, so now let’s discuss a few real-life applications of this database system. Here are a few real-life applications Of MongoDB By Some Prominent Companies.
1) India’s Aadhaar
Aadhaar is a fantastic example of a real-world MongoDB use case. Aadhaar is India’s Unique Identification Project and the world’s most extensive Biometrics Database System. The program launched in 2009 has collected demographic and biometric information from over 1.2 billion people. Aadhaar relied on MongoDB, among other database systems like HBase, MySQL, and Hadoop, to store this massive amount of data. However, MongoDB was one of the database systems first purchased to power the search strategy.
Another real-world MongoDB use case is Forbes. When a story becomes viral, people resort to every available website to get details. Therefore, it is essential for publishers to be alert and give shareable information as soon as possible to keep their readers informed.
This prompted Forbes to find practical solutions to boost its Content Engagement Rate. Forbes constructed its CMS and mobile application in two months using MongoDB. They had to redesign their website and switch to MongoDB to upload content from anywhere in the world efficiently.
Their editors also took advantage of MongoDB’s flexible structure to deliver dynamic quality material promptly to their viewers. This brave action eventually paid off. With this, they could eliminate poor existing practices while lowering overhead expenses.
MetLife is a market leader in employee insurance, benefit plans, and pensions. They serve over 90 million clients across the Middle East, Europe, Asia, Latin America, Japan, and the United States. MetLife’s sophisticated customer service solution, “The Wall,” is built on MongoDB.
The Wall is a tool that offers a consolidated view of MetLife Customers’ payments, policy statements, and other information. It functions like Facebook’s Wall, which gathers data from 70 historical systems and integrates it into a database table. The Wall has a capacity of 24 TB and is distributed across six different servers in two Data Management Centers. Currently, MetLife is looking to further improve its service with several Big Data initiatives, including MongoDB-based apps.
Many retail businesses need Real-time Analytics. This requires that their apps remain relevant and always available online, with no interruption. This is because slow response time leads to a lot of revenue loss in the retail industry due to the cutthroat competition.
When consumers have several alternatives, they will not hesitate to switch to a more reliable service provider. For example, Otto is a major e-commerce company with a massive user base looking to meet and exceed its customers’ expectations. However, prompt response time was a significant challenge because their website has over 500 companies.
Otto is a classic MongoDB use case where they used MongoDB to lower their response time to between 1 to 2 seconds to solve this problem. They had to rebuild their entire catalog application. They used MongoDB because of its customizable schema capabilities, reliability, and growth characteristics.
Shutterfly is a major Digital Picture Exchange and Private Publishing Firm with over 6 billion photographs and a processing volume of up to 10,000 calculations every second. It is one of the businesses that switched from Oracle to MongoDB.
During their transition to MongoDB, it became clear that running non-Relational Databases would better meet the company’s data demands, potentially enhancing programmer efficiency and customizability.
Before choosing MongoDB, Shutterfly investigated several other database systems, including BerkeleyDB and Cassandra. However, the firm settled for MongoDB while implementing it to data relevant to uploaded photographs. Still, the conventional RDBMS remains in place for aspects of the process that require a fuller transactional architecture, such as payment and account administration.
Shutterfly is pleased with its choice to adopt MongoDB, as noted by its data architect, Kenny Gorman, who said the firm believes in picking the right technology for the task. His statement showed that MongoDB was an excellent match, although not without tradeoffs. For example, many issues cropped up before they streamlined their services to match their users’ needs.
Major gaming firms like FACEIT and SEGA have effectively used MongoDB to improve their consumers’ interactive experiences. Underneath the shell, FACEIT relies on MongoDB as its primary Database System. In addition, MongoDB manages the orchestration of services between gamers, groups, and contests.
FACEIT even uses MongoDB to maintain its User Profile and Tournament Data. Users’ live streaming data is saved in MongoDB, and other metrics are used to measure players’ activity and interaction. Due to MongoDB’s Flexible Structure and Extensive Query Model, FACEIT could keep user profiles more effectively.
7) Weather Channel
While running its website, weather.com, the Weather Channel had problems servicing a massive clientele because it used a standard RDBMS system. However, MongoDB enabled them to develop their Smartphone application that serves over 40 million active users and provides Real-time Meteorological Data to its clients.
They also employed MongoDB’s Scalable Solution and MapReduce Functionalities to perform Real-time Analytics and forecasts based on weather data obtained. The prototype version that had previously taken weeks to develop was delivered in just a few hours. This gave The Weather Channel an edge over the competition.
In this article, you have learned about the popular Real-World MongoDB Use Cases. Although it took some time for MongoDB to gain traction, its reputation has risen tremendously in recent years. MongoDB has become one of the most widely used databases because of its Customizable Design, MapReduce functionality, and best-in class performance. Interestingly, MongoDB was recognized by a database rating service as the best performing platform in 2019, after DB-engine. This led to a massive increase in its adoption. Nowadays, many more companies want to associate themselves with MongoDB.
Apart from MongoDB, you would be using several applications and databases across your business for Marketing, Accounting, Sales, Customer Relationship Management, etc. To get a complete overview of your business performance, it is important to consolidate data from all these sources. To achieve this you need to assign a portion of your Engineering Bandwidth to Integrate Data from all sources, Clean & Transform it, and finally, Load it to a Cloud Data Warehouse or a destination of your choice for further Business Analytics. All of these challenges can be comfortably solved by a Cloud-Based ETL tool such as Hevo Data.
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