introduction.txt

.. _intro-to-mongodb:

=======================
Introduction to MongoDB
=======================

.. default-domain:: mongodb

.. facet::
   :name: genre
   :values: reference

.. meta:: 
   :description: Learn about the advantages of MongoDB document databases.
   :keywords: atlas

.. contents:: On this page
   :local:
   :backlinks: none
   :depth: 1
   :class: singlecol

You can create a MongoDB database in the following environments:

.. include:: /includes/fact-environments.rst

To learn more about creating a MongoDB database with the Atlas UI,
see :atlas:`Get Started with Atlas </getting-started>`.

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.

.. include:: /images/crud-annotated-document.rst

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 :ref:`collections <collections>`.
Collections are analogous to tables in relational databases.

In addition to collections, MongoDB supports:

- Read-only :doc:`/core/views` 

- :doc:`/core/materialized-views` 

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 :ref:`read and write
operations (CRUD) <crud>` as well as:

- :ref:`Data Aggregation <aggregation-pipeline>`

- :ref:`Text Search <text-search>` and :doc:`Geospatial Queries
  </tutorial/geospatial-tutorial>`.

.. seealso::
   
   - :doc:`/reference/sql-comparison`
   - :doc:`/reference/sql-aggregation-comparison`
   
High Availability
~~~~~~~~~~~~~~~~~

MongoDB's replication facility, called :doc:`replica set
</replication>`, provides:

- *automatic* failover

- data redundancy.

A :doc:`replica set </replication>` 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:

- :ref:`Sharding <sharding-introduction>` distributes data across a
  cluster of machines.

- Starting in 3.4, MongoDB supports creating :ref:`zones
  <zone-sharding>` of data based on the :term:`shard key`. In a
  balanced cluster, MongoDB directs reads and writes covered by a zone
  only to those shards inside the zone. See the :ref:`zone-sharding`
  manual page for more information.


Support for Multiple Storage Engines
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

MongoDB supports :doc:`multiple storage engines
</core/storage-engines>`:

- :doc:`/core/wiredtiger` (including support for
  :doc:`/core/security-encryption-at-rest`)

- :doc:`/core/inmemory`.

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

.. toctree::
   :titlesonly:
   :hidden:

   Get Started </tutorial/getting-started>
   Create an Atlas Free Tier Cluster <https://docs.atlas.mongodb.com/getting-started/>
   MongoDB Shell (mongosh) <https://www.mongodb.com/docs/mongodb-shell/>
   Databases & Collections </core/databases-and-collections>
   Documents </core/document>
   Query API </query-api>
   BSON Types </reference/bson-types>