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Introduction to MongoDB

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  • Document Database
  • Key Features

Welcome to the MongoDB 5.3 Manual! MongoDB is a document database designed for ease of development and scaling.

The manual describes key concepts in MongoDB such as:

  • The query API

  • Operational and administrative references

  • Tutorials and procedures

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.

A MongoDB document.

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.

MongoDB stores documents in collections. Collections are analogous to tables in relational databases.

In addition to collections, MongoDB supports:

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.

The MongoDB Query API supports read and write operations (CRUD) as well as:


See also:

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.

MongoDB provides horizontal scalability as part of its core functionality:

  • Sharding distributes data across a cluster of machines.

  • Starting in 3.4, MongoDB supports creating zones of data based on the shard key. In a balanced cluster, MongoDB directs reads and writes covered by a zone only to those shards inside the zone. See the Zones manual page for more information.

MongoDB supports multiple storage engines:

In addition, MongoDB provides pluggable storage engine API that allows third parties to develop storage engines for MongoDB.

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