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Understanding MongoDB

MongoDB is an agile and scalable NoSQL database. The name Mongo comes from the word humongous. MongoDB is based on the NoSQL document store model, in which data objects are stored as separate documents inside a collection instead of in the traditional columns and rows of a relational database. The documents are stored as binary JSON or BSON objects.

The motivation of the MongoDB language is to implement a data store that provides high performance, high availability, and automatic scaling. MongoDB is extremely simple to install and implement, as you will see in upcoming hours. MongoDB offers great website back-end storage for high-traffic websites that need to store data such as user comments, blogs, or other items because it is fast, scalable, and easy to implement.

The following are some additional reasons MongoDB has become the most popular NoSQL database:

  • Document oriented: Because MongoDB is document oriented, the data is stored in the database in a format that is very close to what you will be dealing with in both server-side and client-side scripts. This eliminates the need to transfer data from rows to objects and back.
  • High performance: MongoDB is one of the highest-performing databases available. Especially in today’s world, where many people interact with websites, having a back end that can support heavy traffic is important.
  • High availability: MongoDB’s replication model makes it easy to maintain scalability while keeping high performance and scalability.
  • High scalability: MongoDB’s structure makes it easy to scale horizontally by sharding the data across multiple servers.
  • No SQL injection: MongoDB is not susceptible to SQL injection (putting SQL statements in web forms or other input from the browser that compromises the DB security) because objects are stored as objects, not by using SQL strings.

Understanding Collections

MongoDB groups data through collections. A collection is simply a grouping of documents that have the same or a similar purpose. A collection acts similarly to a table in a traditional SQL database. However, it has a major difference: In MongoDB, a collection is not enforced by a strict schema. Instead, documents in a collection can have a slightly different structure from one another, as needed. This reduces the need to break items in a document into several different tables, as is often done in SQL implementations.

Understanding Documents

A document is a representation of a single entity of data in the MongoDB database. A collection consists of one or more related objects. A major difference exists between MongoDB and SQL, in that documents are different from rows. Row data is flat, with one column for each value in the row. However, in MongoDB, documents can contain embedded subdocuments, providing a much closer inherent data model to your applications.

In fact, the records in MongoDB that represent documents are stored as BSON, a lightweight binary form of JSON. It uses field:value pairs that correspond to JavaScript property:value pairs that define the values stored in the document. Little translation is necessary to convert MongoDB records back into JSON strings that you might be using in your application.

For example, a document in MongoDB might be structured similar to the following, with name, version, languages, admin, and paths fields:

  name: "New Project",
  version: 1,
  languages: ["JavaScript", "HTML", "CSS"],
  admin: {name: "Brad", password: "****"},
  paths: {temp: "/tmp", project:"/opt/project", html: "/opt/project/html"}

Notice that the document structure contains fields/properties that are strings, integers, arrays, and objects, just as in a JavaScript object. Table 11.1 lists the different data types for field values in the BSON document.

TABLE 1.1 MongoDB Data Types and Corresponding ID Number











Binary data


Object ID








Regular expression






JavaScript (with scope)


32-bit integer




64-bit integer


Min key


Max key


The field names cannot contain null characters, dots (.), or dollar signs ($). In addition, the _id field name is reserved for the Object ID. The _id field is a unique ID for the system that consists of the following parts:

  • A 4-byte value representing the seconds since the last epoch
  • A 3-byte machine identifier
  • A 2-byte process ID
  • A 3-byte counter, starting with a random value

The maximum size of a document in MongoDB is 16MB, to prevent queries that result in an excessive amount of RAM or intensive hits to the file system. You might never come close to this, but you still need to keep the maximum document size in mind when designing some complex data types that contain file data into your system.

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