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Mongodb Tutorial Introduction

Introduction to MongoDB

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What is MongoDB?

MongoDB is an Open Source database written in C++.

Drivers and client libraries are typically written in their respective languages, although some drivers use C extensions for better performance.

If the load increases, by adding more nodes (such as a computer), the performance can be retained.

It can be used to store data for very high-performance applications (for example Foursquare is using it in production).

MongoDB does not support SQL It supports a rich, ad-hoc query language of its own.

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MongoDB stores data as documents. So it is a document oriented database.

FirstName="Arun", Address="St. Xavier's Road", Spouse=[{Name:"Kiran"}], Children=[{Name:"Rihit", Age:8}].
FirstName="Sameer",Address="8 Gandhi Road".

Notice there are two different documents (separated by "."). Storing data in this fashion is called as document oriented database. MongoDB is a document oriented database.

Key Features

Since MongoDB offers a Document oriented storage, It is simple and easily programmable.

  • You can set an index on any attribute of a MongoDB record (as FirstName="Sameer",Address="8 Gandhi Road"), with respect to which, a record can be sort quickly and ordered.
  • You can set mirror across local as well as wide area networks, which makes it easily scalable.
  • If load increases (more storage space, more processing power), it can be distributed to other nodes across computer networks. This is called as sharding.
  • MongoDB supports rich query to fetch data from the database.
  • MongoDB supports replacing an entire document (database) or some specific fields with it's update() command.
  • MongoDB supports Map/Reduce framework for the batch processing of data and aggregation operation. Here is brief of how Map/Reduce works :
  • Map : A master node takes an input. Splits it into smaller sections. Sends it to the associated nodes.
  • These nodes may perform the same operation in turn to send those smaller section of input to other nodes. It processes the problem (taken as input) and sends it back to the Master Node.
  • Reduce : The master node aggregates those results to find the output.
  • GridFS specification of MongoDB supports storage of very large files.
  • MongoDB supports various programming languages like C, C# and .NET, C++, Erlang, Haskell, Java, Javascript, Perl, PHP, Python, Ruby, Scala (via Casbah).
  • It supports Server-side JavaScript execution. Which allows a developer to use a single programming language for both client and server side code.
  • MongoDB is easily installable.

MongoDB Fundamentals : Frequently Asked Questions

What kind of database is MongoDB?
MongoDB is a document-oriented DBMS. Think of MySQL but with JSON-like objects comprising the data mode, rather than RDBMS tables. MongoDB supports neither joins nor transactions.

Does MongoDB database stores its data in tables?
A MongoDB database stores its data in collections instead of tables, which are the rough equivalent of RDBMS tables.

Do MongoDB databases have schemas?
MongoDB uses dynamic schemas. Without defining the structure you can create collections, i.e. the fields or the types of their values, of the documents in the collection. You can change the structure of documents simply by adding new fields or deleting existing ones.

Which programming languages can be used to work with MongoDB?
MongoDB client drivers exist for all of the most popular programming languages. See the latest list of drivers for details.

Does MongoDB support SQL?

What are typical uses for MongoDB?
Content management systems, mobile applications, gaming, e-commerce, analytics, archiving, and logging.

Does MongoDB support transactions?
No. However, MongoDB does provide atomic operations on a single document.

Does MongoDB require a lot of RAM?
Not necessarily. It's certainly possible to run MongoDB on a machine with a small amount of free RAM. MongoDB automatically uses all free memory on the machine as its cache.

Does MongoDB handle caching?
Yes. MongoDB keeps all of the most recently used data in RAM. If you have created indexes for your queries and your working data set fits in RAM, MongoDB serves all queries from memory.

What are the limitations of 32-bit versions of MongoDB?
Changed in version 3.0: Commercial support is no longer provided for MongoDB on 32-bit platforms (Linux and Windows).


Development of MongoDB began in October 2007 by 10gen. The first public release was in February 2009.

Obtain MongoDB

You can download MongoDB from http://www.mongodb.org/downloads. As of this writing, it supports following platforms:

  • OS X 32-bit
  • OS X 64-bit
  • Linux 32-bit
  • Linux 64-bit
  • Windows 32-bit
  • Windows 64-bit
  • Solaris i86pc
  • Solaris 64
  • You can download the source and install MongoDB from that too.

MongoDB : Databases, Schemas, and Tables

Databases : MongoDB is a document-oriented DBMS, with JSON-like objects comprising the data model, rather than RDBMS tables. MongoDB does not support joins nor transactions. However, it features secondary indexes, an expressive query language, atomic writes on a per-document level, and fully-consistent reads. MongoDB uses BSON, a binary object format similar to, but more expressive than JSON.

Schemas : MongoDB uses dynamic schemas. We can create collections without defining the structure, i.e. the fields or the types of their values, of the documents. You can change the structure of documents simply by adding new fields or deleting existing ones. Documents in a collection need unique set of fields.

Tables : MongoDB database stores its data in collections not in tables The collections are the rough equivalent of RDBMS tables. A collection holds one or more documents, which corresponds to a record or a row in a relational database table, and each document has one or more fields, which corresponds to a column in a relational database table.

MongoDB and ACID transactions

MongoDB does not support multi-document transactions but provides atomic operations on a single document. Often these document-level atomic operations are sufficient to solve problems that would require ACID transactions in a relational database.

In MongoDB, you can embed related data in nested arrays or nested documents within a single document and update the entire document in a single atomic operation. Relational databases might represent the same kind of data with multiple tables and rows, which would require transaction support to update the data atomically.

MongoDB allows clients to read documents inserted or modified before it commits these modifications to disk, regardless of write concern level or journaling configuration. Applications may observe two classes of behaviors :

  • MongoDB will allow clients to read the results of a write operation before the write operation returns for systems with multiple concurrent readers and writers
  • If the MongoDB terminates before the journal commits, even if a write returns successfully, queries may have read data that will not exist after the MongoDB restarts.

Other database systems refer to this isolation semantics as read uncommitted. For all inserts and updates, MongoDB modifies

  • each document in isolation
  • clients never see documents in intermediate states

For multi-document operations, MongoDB does not provide any multi-document transactions or isolation. When MongoDB returns a successful journaled write concern, the data is fully committed to disk and will be available after MongoDB restarts. For replica sets, write operations are durable only after a write replicates and commits to the journal of a majority of the voting members of the set.

MongoDB and caching

MongoDB has no configurable cache. MongoDB uses all free memory on the system automatically by way of memory-mapped files. Operating systems use the same approach with their file system caches. MongoDB keeps all of the most recently used data in RAM. If you have created indexes for your queries and your working data set fits in RAM, MongoDB serves all queries from memory.

MongoDB does not implement a query cache, it serves all queries directly from the indexes and/or data files.


There are several tools available for managing MongoDB.


Network and System monitoring tool Munin has a plugin available for MongoDB.

Distributed high-performance system monitoring tool Gangila has a plugin available for MongoDB.

Open source web based graphic tool Cacti, used to graph CPU load, network bandwidth utilization has a plugin available for MongoDB.


  • Fang of Mongo is a web-based user interface built with Django and jQuery.
  • Futon4Mongo is a clone of the CouchDB Futon web interface for MongoDB.
  • Mongo3 is a Ruby-based interface.
  • MongoHub is a native OS X application for managing MongoDB.
  • Opricot is a browser-based MongoDB shell written in PHP.
  • phpMoAdmin is a PHP based MongoDB management tool.
  • MongoVUE is a Windows based GUI to work with MongoDB.
  • RockMongo is a PHP based MongoDB administration GUI tool.

MongoDB in production

Here is a list of a few MongoDB production deployment :

  • Craiglist uses MongoDB to archive their billions of records.
  • FourSquare, a location-based social networking site, uses MongoDB to shrade there data over a number of machines on Amazon EC2.
  • Shutterfly, an Internet-based social expression, and personal publishing service, uses MongoDB for various persistent data storage requirements.
  • bit.ly, a web based url shortening service, uses MongoDB for storing their data.
  • spike.com, a MTV Network's associate, uses MongoDB.
  • Intuit, a large provider of software and services for small businesses and individuals, uses MongoDB to track user engagement and activity in real-time across its network of websites for small businesses.
  • sourceforge.net, a site to find, create and publish Open Source Software for free, uses MongoDB for back-end storage.
  • etsy.com, a site to buy and sell handmade items, uses MongoDB.
  • The New York Times, one of the leading online news portal, is using MongoDB in a form-building application for photo submissions.
  • CERN, the prestigious particle Physics research institute, uses MongoDB for Large Hadron Collider data.

What you will learn

w3resource's MongoDB tutorial is first of it's kind on the internet. This is a comprehensive tutorial on MongoDB, covering hundreds of examples on how to use it with PHP.

After reading this tutorial, you will be able to install and develop Web base applications using MongoDB

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