Introduction to MongoDB
On this page
Important
MongoDB 6.1 is a rapid release and is only supported for MongoDB Atlas. MongoDB 6.1 is not supported for use on-premises. For more information, see MongoDB Versioning.
Document Database
A record in MongoDB is a document, which is a data structure composed of field and value pairs. MongoDB documents are similar to JSON objects. The values of fields may include other documents, arrays, and arrays of documents.
The advantages of using documents are:
Documents correspond to native data types in many programming languages.
Embedded documents and arrays reduce need for expensive joins.
Dynamic schema supports fluent polymorphism.
Collections/Views/On-Demand Materialized Views
MongoDB stores documents in collections. Collections are analogous to tables in relational databases.
In addition to collections, MongoDB supports:
Read-only Views (Starting in MongoDB 3.4)
On-Demand Materialized Views (Starting in MongoDB 4.2).
Key Features
High Performance
MongoDB provides high performance data persistence. In particular,
Support for embedded data models reduces I/O activity on database system.
Indexes support faster queries and can include keys from embedded documents and arrays.
Query API
The MongoDB Query API supports read and write operations (CRUD) as well as:
Tip
See also:
Learn about the latest query language features with the MongoDB Query Language: What's New presentation from MongoDB.live 2020.
High Availability
MongoDB's replication facility, called replica set, provides:
automatic failover
data redundancy.
A replica set is a group of MongoDB servers that maintain the same data set, providing redundancy and increasing data availability.
Horizontal Scalability
MongoDB provides horizontal scalability as part of its core functionality:
Support for Multiple Storage Engines
MongoDB supports multiple storage engines:
WiredTiger Storage Engine (including support for Encryption at Rest)
In addition, MongoDB provides pluggable storage engine API that allows third parties to develop storage engines for MongoDB.