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Database

MongoDB

By MongoDB, Inc.

BeginnerTool2.6K learners

MongoDB is an open-source, document-oriented NoSQL database that stores data as flexible, JSON-like documents (BSON) rather than rows and columns in fixed tables.

Definition

MongoDB is an open-source, document-oriented NoSQL database that stores data as flexible, JSON-like documents (BSON) rather than rows and columns in fixed tables.

Overview

MongoDB was first released in 2009 by the company then known as 10gen, later renamed MongoDB, Inc., as part of a broader effort to build easier, more scalable web infrastructure. Its document model was designed to map more naturally onto how developers think in objects and JSON, especially in JavaScript-based stacks. Instead of enforcing a fixed schema across rows in a table like MySQL or PostgreSQL, MongoDB stores records as documents that can nest arrays and sub-objects and vary in structure from one document to the next. Collections of documents can be indexed, sharded across servers for horizontal scaling, and replicated for high availability, and the query language uses JSON-like filter documents rather than SQL. MongoDB became closely associated with the MEAN and MERN stacks—paired with Express.js, React, and Node.js—where developers typically access it through an ODM like Mongoose. Beyond self-hosting, MongoDB Atlas offers it as a fully managed cloud database across major cloud providers, and SkillVeris's Project: Build a Full-Stack To-Do App with React, Node.js and MongoDB walks through a typical MERN-stack build.

Key Features

  • Flexible, schema-less document model based on BSON (binary JSON)
  • Horizontal scaling through built-in sharding
  • Replica sets for automatic failover and high availability
  • Rich query language supporting filtering, aggregation pipelines, and indexing
  • Native support for nested arrays and sub-documents
  • Change streams for reacting to data changes in real time
  • Full-text and geospatial indexing options
  • MongoDB Atlas managed service across AWS, Azure, and Google Cloud
  • Strong ecosystem of drivers and ODMs across most programming languages

Use Cases

Backing web and mobile applications with rapidly evolving data models
Storing content that naturally maps to nested JSON, like product catalogs
Powering real-time applications with change streams
Serving as the database layer in MEAN/MERN-stack applications
Running content management systems and user-generated content platforms
Storing IoT and event data at high write volume
Building catalogs and recommendation systems with flexible schemas
Running analytics via MongoDB's aggregation framework

History

MongoDB is a document-oriented NoSQL database that stores data in flexible, JSON-like documents rather than rigid relational tables. It was created by the company originally named 10gen, founded in 2007 in New York City by Dwight Merriman, Eliot Horowitz, and Kevin Ryan — veterans of the ad-tech company DoubleClick who had hit the scaling limits of relational databases. Initially building a platform-as-a-service, the team recognized that their database layer was the most valuable piece and pivoted to it, releasing MongoDB as open source in 2009 (the name derives from "humongous"). The company renamed itself MongoDB Inc. in 2013, and MongoDB became one of the most popular NoSQL databases and a widely used choice for modern applications.

Sources

Frequently Asked Questions

From the Blog

Frequently Asked Questions

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Does SkillVeris have a tech blog, and what does it cover?
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What is the SkillVeris tech glossary and how big is it?
The SkillVeris glossary is a free reference of roughly 2,000-plus technology terms, each with a clear plain-language definition. It spans AI, programming, web, DevOps, cloud, security and database vocabulary, so whenever a lesson, article or job description uses jargon you do not recognise, the glossary gives you a fast, reliable answer.
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Search the SkillVeris glossary, which holds around 2,000-plus terms with concise, plain-language definitions. Each entry gets to the point in its first sentence, then links to related reading like blog posts or study notes for deeper context. It is faster and more consistent than sifting through scattered search results.
Is the SkillVeris blog good for beginners learning to code?
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Can cheat sheets replace full courses for learning a language?
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Does the glossary cover AI and machine learning terms?
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Are there cheat sheets for interview preparation?
Cheat sheets work well as interview-day refreshers because they compress syntax, commands and key concepts into scannable references. For dedicated preparation, combine them with the SkillVeris interview questions feature, which includes readiness scoring, plus study notes for depth. Reviewing a relevant cheat sheet just before an interview steadies recall under pressure.
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How is the SkillVeris glossary different from Wikipedia?
The glossary is purpose-built for learners: definitions are short, plain-language and answer-first, sized for a quick lookup mid-lesson rather than a deep encyclopedic read. Entries also cross-link to related SkillVeris study notes, blog posts and courses, so a definition becomes a doorway into structured learning instead of a dead end.
Do blog articles use the Learn Through Hobbies method?
Many blog articles teach technical topics through hobby analogies, a hallmark of the SkillVeris blog, so you will find articles explaining programming through cricket, machine learning through music, or system design through cooking. The analogy is the teaching device; the article still delivers the real technical concept underneath.
Where can I find quick programming references while coding?
Open the SkillVeris cheat sheets, which are built exactly for that moment: compact, scannable references for syntax, commands and common patterns across languages and tools. Keep the relevant sheet in a browser tab while you work in Code Lab or your own editor, and dip into the glossary for terminology.
Is there a glossary entry for terms I meet in job descriptions?
Very likely yes, with roughly 2,000-plus terms across AI, programming, web, DevOps, cloud, security and databases, the glossary covers most jargon that appears in tech job descriptions. Decoding a listing this way helps you judge role fit honestly and prepares you to discuss those terms in interviews.
Are the blog articles written for the Indian tech audience?
The blog serves Indian learners plus a worldwide audience. Content stays globally relevant while acknowledging realities that matter in India, such as free access being essential for students and freshers, and career guidance that connects naturally to the SkillVeris jobs portal, which aggregates roles across India, UK, USA, Germany and Remote.
Can I suggest a topic for the blog or glossary?
SkillVeris content grows in response to what learners need, so feedback is welcome through the platform's support channels. If a term is missing from the glossary or a topic deserves an article, telling the team helps prioritise it. Meanwhile, the AI Mentor can answer the question immediately, 24/7, at any depth.
Do cheat sheets and glossary entries link to deeper learning?
Yes, every cheat sheet and glossary entry carries related reading links into study notes, blog articles and courses, plus concept hashtags for discovering similar content. This cross-linking means a thirty-second lookup can smoothly become a structured learning session whenever you decide you want more than a quick answer.
What makes SkillVeris programming references trustworthy?
The references are written to strict internal quality standards, kept consistent with the platform's 37 live courses, and never padded with invented statistics or hype. Definitions and cheat sheets are reviewed against the same content contracts that govern courses, and the answer-first style makes any inaccuracy easy to spot and correct.
How do the blog, glossary and cheat sheets fit into my learning routine?
Use them as satellites around your main course: read blog articles for context and motivation, hit the glossary the instant jargon appears, and keep cheat sheets open while coding. Together with study notes, Code Lab and the 24/7 AI Mentor, they turn passive reading into a complete, free learning system.

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