What is MongoDB?
Known as the developer data platform, MongoDB provides services and tools to build applications fast, enabling you to achieve both performance and scale. In this article, we’ll discuss the key features of MongoDB and compare it to other database management systems such as MySQL and PostgreSQL. We’ll also explore some use cases for MongoDB, the costs associated with using the platform, and if MongoDB may be the database for your needs.
What is MongoDB, and What are its Key Features?
MongoDB is a scalable and flexible document database built by developers for developers. With MongoDB, you can handle complex requirements at scale, and you can access your data in powerful ways via ad hoc queries, indexing, and real-time aggregation. Since MongoDB is a distributed database at its core, it comes with built-in features like high availability, horizontal scaling, and geographic distribution.
MongoDB is a NoSQL-based system that uses its own query language, MQL. A NoSQL database is a non-relational database. NoSQL databases may be referred to as not only SQL or non-SQL databases. They are non-tabular and store data differently than relational tables. For example, MongoDB does not require the description of a table scheme.
NoSQL databases give developers a lot of flexibility because they allow them to store large amounts of unstructured data. Using a flexible data model, the NoSQL approach allows you to deploy a scalable database storage system.
Based on their data model, NoSQL databases come in various types, such as document databases, key-value databases, wide-column stores, and graph databases. MongoDB is a document-oriented database program that uses JSON-like documents with optional schemas.
The MongoDB community comprises over 1 million members, ensuring easy access to expert tips and advice. MongoDB provides drivers for more than 10 languages, with dozens more built by the community. Browse the MongoDB 12 official libraries, including C, C++, and C#. You can also browse a list of MongoDB community-supported libraries.
MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. Thousands of teams, including Google, eBay, Intuit, SAP, Verizon, and Adobe, trust MongoDB as their database platform.
How is MongoDB Different From Other Database Management Systems
The main difference between MongoDB and other database management systems is it’s considered a non-relational database. Other options, like MySQL and PostgreSQL, are both relational databases. Let’s dig deeper into the differences between MongoDB, MySQL, and PostgreSQL.
MySQL uses Structured Query Language (SQL) to interact with the database and is a relational database management system (RDBMS), while MongoDB is a NoSQL-based system.
The main difference between a relational database management system and a NoSQL database is the way the data is modeled in the database. For example, data about a user and their location will be stored differently in the two systems. To store this data in a relational database, like MySQL, you would most likely create two tables, one for Users and one for Location. The Users and Location tables will need to be joined together to retrieve information. However, in a NoSQL document database, like MongoDB, a single document can be retrieved from the database, so no joins are required, enabling faster queries.
Developed in 1986 at the University of California at Berkeley, PostgreSQL is an object-relational database system. Like MySQL, PostgreSQL is a relational database, whereas MongoDB is a document database. Your unique needs will determine whether a relational or document database is best.
MongoDB is best if your focus is time to market, developer productivity, supporting DevOps and agile methodologies, and building to scale with operational efficiency. PostgreSQL may be the better option if you are focused on compatibility, accessing thousands of queries from hundreds of tables, leveraging existing SQL skills, and maximizing SQL’s abilities.
PostgreSQL is based on a scale-up architecture, while MongoDB is based on a scale-out architecture. Based on a tabular, relational data model, PostgreSQL will allow you to run complex SQL queries on your existing applications. If your application needs to scale in the volume of traffic and/or data size and must be distributed across regions, MongoDB can meet your needs automatically.
When considering which database management system is right for you, determine whether you need a relational or non-relational option to meet your needs. Let’s move on to some of the potential applications for MongoDB.
What are Some of the Potential Applications for MongoDB?
Since MongoDB is a general-purpose database, a wide variety of use cases exist. The developer data platform, MongoDB Atlas, MongoDB’s database-as-a-service offering, can be applied to operational, transactional, search, analytical, and mobile use cases. Let’s look at an operational and transactional use case in more detail.
Operational Use Cases
MongoDB maps to your application’s access patterns. With MongoDB, you can use a single query API to meet various query requirements. To help analyze and transform your data, MongoDB can support simple lookups to complex processing pipelines.
MongoDB has helped Volvo better support its customers through enhanced visibility with statistics and visualizations and reduced unnecessary queries. Data for more than one million vehicles worldwide, including 65 million daily events, are all stored on MongoDB Atlas.
Transactional Use Cases
MongoDB’s flexible document data model guarantees millisecond response times at scale. MongoDB includes rich query capabilities such as secondary indexing, joins, and multi-document ACID transactions.
Nationwide, a British financial services provider and the world’s largest building society started using MongoDB Atlas in 2019. With MongoDB Atlas, the Nationwide development team can build applications faster, handle highly diverse real-time data types, and manage applications more efficiently at scale using MongoDB’s flexible data model.
What are the Costs Associated With Using MongoDB?
MongoDB offers three ways to get the platform:
- MongoDB Atlas - a fully managed, global cloud database capable of running on AWS, Azure, and GCP.
- MongoDB Enterprise, their on-premises or private cloud, database solution.
- MongoDB Community Edition - a free edition you can download.
You’ll need to choose which one is best for your environment and specific needs. MongoDB Atlas offers several pricing models.
The Shared plan is free and comes with basic configuration options allowing you to learn and explore the database in a cloud environment. It comes with shared RAM and 512MB to 5GB of storage. It is free forever for free clusters, but you can upgrade to dedicated clusters for full functionality.
If you have serverless applications with variable or infrequent traffic, the Serverless plan may be right for your needs. Pricing for the Serverless plan is based on reads and is $.10 per million reads. Minimal configuration is required, and you get up to 1TB of storage. You only pay for your operations and the scale of the resources based on your workload.
Production applications with advanced workload requirements can benefit from the Dedicated plan. The Dedicated plan starts at $57 per month based on an estimate of $.08 per hour. This plan includes advanced configuration controls such as network isolation and fine-grained access controls. The Dedicated plan comes with 10GB to 4TB of storage and 2GB to 768GB of RAM.
MongoDB Atlas also allows you to customize your database with various tools and services such as Atlas Data Federation, Charts, BI Connector, Online Archive, APP Services, and Support.
MongoDB Enterprise includes MongoDB Enterprise Server and Ops Manager, the management platform for MongoDB, along with additional Enterprise level security features and Kubernetes integration for scaling the database. Pricing for MongoDB Enterprise is specific to your requirements, so pricing is provided through MongoDB sales channels.
Drawbacks Associated with Using MongoDB
One advantage of using a SQL-based database platform is its powerful and well-known query language, resulting in a large community of tools. Since MySQL and PostgreSQL are popular, most development tools and other systems have been tested with them, so most likely, you will not experience any compatibility issues. In contrast, MongoDB uses its own query language, MQL. MQL offers most of the same power and flexibility as SQL, but MQL is not as widely known as SQL.
Unless you’re working on a new application or modernizing an existing one, it may not make sense to move away from using SQL. If you already have applications based on relational data models and teams with SQL expertise, MongoDB may not be a good fit. A SQL relational database is a better option if you have a flat, tabular data model that doesn’t change often and doesn’t need to scale out.
If you’re looking for a document database with a scale-out architecture, MongoDB may be right for you. However, if you are more interested in a relational database with scale-up architecture and want to use existing SQL skills, MySQL or PostgreSQL may be best for you.
MongoDB has a strong developer community, including system integrators and consultants who provide various commercial services. Check out the MongoDB Developer Community forum for insight on popular topics surrounding MongoDB.
Agile development teams can benefit from MongoDB’s flexible schema approach. Since MongoDB offers drivers for all major programming languages, you can immediately build your application without configuring a database. Getting started with MongoDB is as easy as installing it on your Ubuntu 18.04 (or greater) or CentOS 8 machine.
Liquid Web’s VPS Hosting, Cloud Dedicated Servers, or Dedicated Servers offer great solutions for installing MongoDB as well. With AlmaLinux, Ubuntu, and other options available, you can set your environment up the way you want. Contact our sales team for more information.
About the Author: Ronald Caldwell
Ron is a Technical Writer at Liquid Web working with the Marketing team. He has 9+ years of experience in Technology. He obtained an Associate of Science in Computer Science from Prairie State College in 2015. He is happily married to his high school sweetheart and lives in Michigan with her and their children.
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