• Each database is made up of collections, which are made up of documents. Each document is unique, with a distinct amount of fields. Each document’s size and content may differ from one another.
  • The document structure is more similar to how programmers build classes and objects in their different programming languages. Developers frequently claim that their classes have a clear structure with key-value pairs rather than rows and columns.
  • There is no need to establish a schema for the rows (or documents as MongoDB calls them). Fields can be built on the fly instead.
  • MongoDB’s data schema makes it easier to describe hierarchical connections, store arrays, and store other more complicated structures.
  • Scalability — MongoDB settings are incredibly scalable. Companies all across the world have created clusters, with some operating 100 plus nodes and millions of documents in the database.
  • Document-oriented — Because MongoDB is a NoSQL database, rather than storing data in a relational style, it saves it in documents. As a result, MongoDB is extremely adaptive to real-world situations and requirements.
  • MongoDB allows searching by field, range queries, and regular expression searches as well as ad hoc queries. Specific fields inside documents can be returned via queries.
  • Indexing — Indexes may be used to increase the speed of MongoDB searches. An index may be created for any field in a MongoDB document.
  • Replication — With replica sets, MongoDB can provide high availability. Two or more mongo DB instances make up a replica set. At any time, any member of the replica set can operate as the primary or secondary replica. The primary replica is the main server that communicates with the client and handles all read/write activities. Using built-in replication, the secondary replicas keep a copy of the primary’s data. When a primary replica fails, the replica set shifts to the secondary replica, which then becomes the primary server.
  • Load balancing — To grow horizontally, MongoDB employs the idea of sharding, which splits data across several MongoDB instances. MongoDB may be distributed across numerous servers, balancing traffic and/or replicating data to keep the system functioning in the event of hardware failure.




Student at Sri lankan Institute Of Information Technology and working as a trainee at Inexis Consulting

Love podcasts or audiobooks? Learn on the go with our new app.

Recommended from Medium

Beating NumPy performance by extending Python with C

Build your first dashboard using Microsoft Power BI

My Cloud computing journey

Setting up a CI/CD pipeline in Azure DevOps for Azure Functions + Sql Server

Building Cross-platform Dotnet Core Document Scanning with MVC

The pitfalls of scaling on Serverless platforms

Graph — Youngest Common Ancestor

Power Up Your CV With CSS (Part 2)

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Mohomed Irshad

Mohomed Irshad

Student at Sri lankan Institute Of Information Technology and working as a trainee at Inexis Consulting

More from Medium

5 Common REST API Challenges

Authentication & Authorization, Hashing in Web Applications

Communication in Containers