What Is MongoDB & How Can It Help You Build Scalable Apps?

TL;DR: MongoDB is a highly scalable and fault-tolerant tool that supports a flexible data model, helping developers build highly scalable and performant web applications.

By Richard George
16 min read

Data is generated at an unprecedented pace today. It is now essential for applications to be scalable and have the ability to handle large volumes of data. This is where MongoDB comes in, a document-oriented, NoSQL database program that’s gained immense popularity in recent years.

MongoDB offers a flexible data model, a powerful query language, and the ability to scale horizontally across multiple servers, making it an excellent choice for building modern, data-intensive applications.

In this blog post, we will explore MongoDB in detail and how it can help you build scalable apps. We will cover its key features, benefits, drawbacks, and use cases so that you can make an informed decision about whether MongoDB is right for your application development needs. First, let’s start with what MongoDB is, shall we?

What Is MongoDB? 🍃

MongoDB logo

MongoDB is a popular NoSQL document-oriented database system that uses a JSON-like format to store and manage data. Unlike traditional relational databases that use tables, rows, and columns to store data, MongoDB stores data in flexible, dynamic documents that can have varying structures and schemas.

MongoDB offers unparalleled scalability and enables your data to grow with you. Its powerful query language makes it simple for users of any skill level to access complex information quickly, while its flexible modelling capabilities let you tap into the full potential of large-scale datasets.

The common use cases of MongoDB include the development of web applications along with mobile applications and big data environments where data needs to be accessed quickly and efficiently. You can also find it often used in real-time analytics and Internet of Things applications due to its capacity to handle huge volumes of data and high levels of concurrency.

Use Cases ⚒️

MongoDB is a versatile database system that you can use for many applications. Below are five major use cases of MongoDB.

🌐 1. Web Applications

MongoDB is exceptional for storing, retrieving, and analysing data in web applications, such as from user activity logs, sensor data, and other high-volume data sources. Its support for data aggregation and analytics makes it ideal for building web applications that require data analysis. For instance, you can use the system to build a dashboard that visualises data from multiple sources or to build a recommendation engine that suggests products or content to users based on their preferences.

Plus, it provides a flexible and powerful query language that you can use to build APIs that support complex search queries, filtering, and sorting. Real-time data and streaming is also supported, allowing you to build things like chat applications.

📱 2. Mobile Applications

The system provides a flexible data model that can easily adapt to changing application requirements and enables developers to create high-performance, scalable, and reliable mobile applications. By leveraging MongoDB’s flexible schema design, you can quickly add new fields or update existing data models to accommodate new features or changes in the application.

The program also provides a native mobile sync solution called Realm Sync, which allows mobile applications to sync data in real-time with the server and other devices. This can be particularly useful for applications that require real-time collaboration or data sharing, such as chat applications or social networks.

🗃️ 3. Big Data

Not only can MongoDB store large volumes of unstructured or semi-structured data, but it also provides various features for real-time analytics, including aggregation pipelines, text search, and geospatial queries. These let you analyse and gain insights from big data in real-time, making it easier to identify patterns and trends to push data-driven decision making.

Furthermore, the system integrates well with other big data platforms, such as Hadoop and Spark. You get to process and analyse data across multiple systems, making it easier to manage and analyse big data and gain insights from large datasets.

📟 4. Internet of Things (IoT)

You can use the database system to collect, store, and process data (cleaning, filtering, and aggregating data) from various Internet of Things devices, such as sensors, cameras, and other connected devices. On top of that, you can process real-time streams of IoT data and perform real-time analytics, meaning you gain insights into their operations and can take action in real-time. This can be useful in applications such as real-time fraud detection or predictive maintenance.

What is MongoDB? - Man analysing real-time IoT data using the system

When used in conjunction with machine learning platforms, you can also create predictive models based on IoT data. This can help you identify patterns and trends in their operations and make more informed decisions.

💻 5. Content Management

MongoDB can store and retrieve all types of content and handle large volumes of data and content easily. You can then use this to deliver personalised content based on user preferences, history, and behaviour to ensure more relevant and engaging content reaches your target audience. This is particularly effective when used in conjunction with Next.js for eCommerce websites.

You can also use the program to deliver content across multiple channels, including web, mobile, and social media, for a wider reach and improved customer engagement. Additionally, you can improve productivity and ensure consistency in content across all channels using MongoDB to facilitate collaboration among teams working on content creation.

Product Offerings 🗳️

MongoDB offers several products designed to help developers and organisations build, manage, and scale applications. Here are some of their key products and services that you can use:

  • Community Server: This is the free and open-source database server that powers the system. It offers features like replication and a rich query language, making it a powerful tool for building scalable and high-performance applications.
  • Compass: This is a graphical user interface (GUI) tool that makes it easy to visualise and explore data stored in the program. It offers features like real-time data exploration, query optimisation, and schema visualisation to assist both developers and data analysts.
  • Enterprise Advanced Server: This is designed for mission-critical applications that require high performance, scalability, and security. It’s licensed under a commercial license and provides additional features and support beyond what is available in the open-source Community Server.
  • BI Connector: This is a tool that allows business intelligence (BI) tools like Microsoft Power BI to connect to MongoDB databases. It allows organisations to perform ad-hoc queries and analysis on their MongoDB data using their existing BI tools.
  • Atlas: This is the fully-managed and paid version of MongoDB that makes it easy to deploy, manage, and scale databases in the cloud. It integrates natively with Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Other features include automatic scaling, automatic backups, and automated upgrades, making it a great option for businesses that want to focus on building their applications rather than managing their databases.
  • Serverless Atlas: This version of Atlas lets developers run their workloads in a serverless environment, allowing you to focus on the application code without worrying about managing database infrastructure.
  • Atlas Data Federation: This feature of the MongoDB Atlas cloud database service is a serverless, scalable query engine that allows users to seamlessly query and join data from multiple MongoDB Atlas clusters and other data sources such as Amazon S3 or Elasticsearch. It provides a flexible and powerful solution for federating data across multiple MongoDB clusters and other data sources, enabling users to build scalable, distributed, and high-performance applications.
  • Charts: This is a data visualisation tool that allows users to create and share interactive charts, graphs, and dashboards based on data stored in MongoDB databases. It is a part of the MongoDB Atlas cloud database service but can also be deployed on-premises using the MongoDB Charts On-Prem software.
  • Online Archive: This feature of the MongoDB database management system allows users to transparently move infrequently accessed data from their primary database to a less expensive storage tier, such as Amazon S3 or Azure Blob Storage. This brings reduced storage costs while still retaining data access.
  • App Services: This a suite of backend services that enable developers to build and deploy modern applications on the MongoDB Cloud platform. These include Realm, Atlas Search, Data Lake, and Online Archive.
  • Support: This is a suite of comprehensive support services to help you ensure the reliability, availability, and performance of your MongoDB deployments. This includes technical support, cloud support, training and certification, and consulting services.

MongoDB’s products offer a range of benefits, including scalability, flexibility, ease of use, and powerful query and analytics capabilities. Whether you’re building a web application, a mobile app, or a big data solution, it can help you build, manage, and scale your application with ease.

Building Scalable Apps 🧩

MongoDB is designed to help companies build highly scalable applications across multiple servers or clusters that can grow and evolve with their business needs by providing a flexible and scalable data model. Check out the following features that help you use the program to build scalable apps.

📏 Horizontal Scaling

MongoDB supports horizontal scaling, which means you can add more servers to your cluster as your data and traffic volumes grow. It can do this by automatically sharding data, which is a way of distributing data across multiple servers. By splitting data into smaller chunks and then distributing these ‘shards’ across multiple servers in your cluster, the program can balance your workload across multiple servers and help you handle more traffic and data while maintaining performance.

The system also supports replica sets, which provide built-in fault tolerance and high availability. Replica sets allow you to maintain multiple copies of your data across multiple servers, which can help you ensure that your app stays online and available, even in the event of server failures.

⚙️ Automatic Sharding

The system’s automatic sharding feature works by partitioning your data into smaller subsets called “shards”. Each shard contains a subset of your data, and multiple shards are distributed across multiple servers in your cluster. To determine which shard to store each piece of data on, the system uses a shard key — a field in your data that you specify when creating your collection. Data is automatically balanced across the shards to ensure that each contains a similar amount so that queries can be executed quickly and efficiently.

As your data and traffic volumes grow, you can add more servers to your cluster to handle the increased workload. MongoDB will automatically distribute the data across the new servers, meaning you don’t have to write complex sharding logic yourself and save time and effort.

🤸‍♀️ Flexible Data Model

MongoDB’s document-based data model uses a dynamic schema, which means that you don’t have to define a rigid schema upfront. Instead, you can store data in flexible JSON-like documents, and the schema can evolve over time as your data changes. By storing related data in embedded documents within a single document, you can reduce the number of queries you need to make and simplify your data model. With it, you’re able to easily adapt to changing data requirements and add new features without making significant changes to your database schema. 

You can also update specific fields within a document without having to rewrite the entire document. This means that you can make changes to your data without worrying about schema migrations, which can be time-consuming and error-prone. Furthermore, MongoDB’s powerful Aggregation Framework allows you to perform complex queries and data analysis. This can be particularly useful when dealing with large volumes of data.

💬 Expressive Query Language

The database system’s rich and expressive query language lets you make complex queries on your data using a variety of operators and functions to filter, sort, and aggregate your data in a flexible and efficient way. You can perform ad hoc queries on your data without having to define a schema upfront. This means that you can quickly iterate on your queries and refine them as needed, which can be particularly useful when dealing with large volumes of data.

MongoDB icon in 3D

Another beneficial feature is that MongoDB’s query optimiser automatically chooses the most efficient query plan based on your data and your query requirements. This helps improve query performance and reduce query latency. Indexing on any field in a document is also supported, and combined with the database’s powerful Aggregation Framework, you can perform complex queries and data analysis.

🤝 Community Support

MongoDB has comprehensive and up-to-date documentation that can help you get started quickly and learn about its various features and capabilities. The system also has an active community of users who are willing to help and share their knowledge. You can make enquiries, get counsel, and share experiences on the community forums. You can also use MongoDB University, a brilliant resource that provides free online courses and training resources to help your developers learn how to use the database system effectively.

Additionally, MongoDB Atlas is a fully managed cloud database service that provides you with a highly available, scalable, and secure database platform. It includes features like automated backups, automated scaling, and a global network of data centres. The also offers professional support and consulting services for enterprise customers. This includes access to a dedicated support team, 24/7 emergency support, and personalised advice and guidance.

Thus, MongoDB’s built-in scalability features, flexible data model, powerful query language, and community support make it a great pick for building scalable apps. With this system, you can easily scale your apps as your data and traffic volumes grow without having to worry about performance or stability issues.

What Sets It Apart? 🦄

MongoDB is different from other database systems in several ways. Firstly, it uses a document data model that allows for flexible and dynamic schemas. This is in contrast to relational databases, which use a fixed schema that requires data to fit into tables with predefined columns. As such, developers can store and retrieve data in a more natural and intuitive way, which can lead to faster development and easier maintenance.

Its powerful and expressive query language is another way MongoDB stands out. This allows developers to perform complex queries on their data, supporting a wide range of query operations, including text search, geospatial queries, and aggregation pipelines. This makes it an amazing tool for data analysis and business intelligence.

The database system is also a sound option for apps that require the handling of large datasets and high traffic loads because it’s designed specifically to be highly scalable and highly available, with built-in features like automatic failover and replication. This means you can easily scale horizontally across multiple servers, and your data is always available, even in the event of a hardware or network failure.

Finally, its large and active community of developers and users means that there are plenty of resources available for learning and troubleshooting. The community also contributes to the development of new features and tools, which helps keep MongoDB at the forefront of database technology.

Drawbacks Of MongoDB ⛔

While MongoDB has many benefits, there are also some drawbacks to consider.

Data durability can be a concern because, by default, the program uses write acknowledgment (also known as write concern) settings that prioritise write speed over data durability. This means that in certain failure scenarios, such as a sudden power outage, some data may be lost. However, you can mitigate this by configuring the system’s write concern settings to ensure data durability.

Another potential drawback is that MongoDB can consume a large amount of memory, especially when used in a sharded environment. You can mitigate this by configuring its cache size and using appropriate hardware resources.

As with any new system, the learning curve can also be an initial point of concern. MongoDB’s document-oriented data model and query language can be different from what developers are used to with relational databases.

What is MongoDB? - Man coding on computer using the database

One more downside is that while MongoDB has support for multi-document transactions, its support for distributed transactions is limited, which can make it challenging to maintain data consistency in highly distributed environments.

The final major potential disadvantage is the pricing and commercial offerings (discussed in the next section). While the MongoDB community edition is open-source and free to use, the other commercial offerings, such as MongoDB Atlas, can be expensive depending on the size and complexity of your deployment.

Despite such potential drawbacks to using MongoDB, you can often mitigate them with careful planning, configuration, and development practices.

Pricing Options 💸

Here are the main pricing options for MongoDB as of March 2023:

  • Community Edition: Free and open-source, available for anyone to use
  • Compass: Free to download and use
  • Enterprise Advanced Server: Varies depending on your needs and requirements
  • BI Connector: Varies depending on your needs and requirements
  • Atlas: AU $86.55 per month
  • Serverless Atlas: AU $0.15 per 1 million reads
  • Atlas Data Federation: AU $7.59 per TB with a 10MB minimum per query
  • Charts: Free for the first 1GB & AU $1.52 beyond 1GB (see their Charts pricing for details)
  • Online Archive: Varies depending on your needs and requirements
  • App Services: Varies depending on your needs and requirements
  • Support: Varies depending on your needs and requirements

MongoDB offers numerous pricing options (all in USD) depending on your needs and usage, including plenty of pay-as-you-go options that can’t be listed here, so you’ll need to check out their website. However, for the most reliable quote based on your region and needs, you’ll need to contact their team.

Final Words: MongoDB 🕵

To summarise, MongoDB is a powerful and flexible database system that offers many benefits for building scalable and data-intensive applications. Its document-oriented data model, expressive query language, and built-in scalability features make it a popular choice among developers and businesses worldwide.

So, if you’re looking to build scalable and high-performance web applications, mobile apps, or a big data solution, this database system is definitely worth considering. Its powerful features and benefits make it a compelling option for a wide range of applications and use cases, and it can help you upgrade your app development, allowing you to build, manage, and scale your application with ease.

Database systems like MongoDB are highly beneficial for driving business growth and success by effectively scaling your software development projects. If you want to learn more about such tech or are unsure if your company will benefit from using it, book a discovery call today. We’ll also happily help you identify problems and offer personalised solutions and recommendations!

Published on March 13, 2023

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