MongoDB vs. SQL/MySQL: Why and When to Use MongoDB

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MongoDB vs. SQL/MySQL: Why and When to Use MongoDB

What is MongoDB?

MongoDB is an open-source and free (published under GNU Affero GLP) document database that allows storing data in JSON-like flexible documents. The leading NoSQL DB makes it easier to work with data by mapping objects in the app code. It provides flexibility, scalability and powerful tools to access and analyze data.

Since the data is stored in ‘flexible’ documents, MongoDB fields can vary, while it also allows changing the data structure over time. At its core MongoDB is a distributed DB, which translates into higher availability and scaling capabilities.

Why Use MongoDB?

MongoDB is considered one of the easiest databases to master, thanks to its simple document model. Although it’s easy to learn and use, MongoDB also offers the capabilities and scalability developers and businesses need to handle complex requirements. Users have the freedom to manage the infrastructure themselves or have MongoDB manage things for them. Some key features of the DB include

  • Fully elastic DBaS, best practices built-in
  • Open-source
  • Cross-platform compatible
  • Replication and failover built right in
  • Horizontal scalability
  • Used in the MEAN stack
  • Compatible with .Net apps and Java
  • End-to-end security
  • Native document validation
  • Schema Exploration
  • Available in more than 10 languages
  • Global Support
  • Management tooling (monitoring, backup and automation)

Who Uses MongoDB?

MongoDB is used by many top organizations from different industries, including enterprises, government institutions and top-tier tech companies. The list of its customers includes facebook, ebay, Google, NOKIA, BARCLAYS and UPS. However, this does not mean that the DB is only meant for large businesses and government agencies as individuals and small and medium businesses can also benefit from the open-source technology.

Choosing MongoDB depends on the kind of data users are dealing with and what they want to do with it. MongoDB is suitable for businesses and individuals dealing with modern unstructured data and real-time analytics. Document-based databases such as MongoDB are designed to meet the challenges of BIG Data and deliver data-driven experiences.

MongoDB vs SQL/MySQL

NoSQL databases offer many advantages over table-based relational databases and are able to handle modern, unstructured and complex data more effectively and efficiently. MongoDB is one of the most popular NoSQL databases and allows storing, processing and analyzing vast amounts of unstructured data by grouping it more logically.

One of the main reasons behind MongoDB’s popularity includes it’s cross-platform computability and powerful built-in features. It provides the speed and flexibility large enterprises need to create customized user experiences and make real-time decisions based on real data. MongoDB is able to meet challenges related to modern big data, which traditional databases either cannot meet at all or cause the bottleneck.

Uses of MongoDB

MongoDB can be used to accomplish a variety of goals including:

  • Store and process large and growing amounts of unstructured data
  • Partition and spread cloud-based storage using built-in and powerful sharding options
  • Quick development and release cycles
  • Database scalability without the need of additional software
  • Real-time analytics and reporting
  • Sensor and location based data capitalization
  • Powering content management systems
  • Faster delivery and updates of mobile apps
  • Personalized user experiences


MongoDB is one of the most popular and widely used NonSQL databases currently available and is a better solution than RDMBSs in various situations. However, there are somethings users need to consider before choosing between MongoDB and SQL databases. This includes the skill sets of teams and tools available to them, the existing network infrastructure/architecture, security requirements and expected data growth.

MongoDB works great for users who expect a high write-load, need high availability (especially in unreliable and unpredictable environments) and need to grow big in less time. The DB is also a better choice if most of the data is location-based or going to be big.

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