Book Image

Web Development with MongoDB and Node - Third Edition

Book Image

Web Development with MongoDB and Node - Third Edition

Overview of this book

Node.js builds fast, scalable network applications while MongoDB is the perfect fit as a high-performance, open source NoSQL database solution. The combination of these two technologies offers high performance and scalability and helps in building fast, scalable network applications. Together they provide the power for manage any form of data as well as speed of delivery. This book will help you to get these two technologies working together to build web applications quickly and easily, with effortless deployment to the cloud. You will also learn about angular 4, which consumes pure JSON APOIs from a hapi server. The book begins by setting up your development environment, running you through the steps necessary to get the main application server up-and-running. Then you will see how to use Node.js to connect to a MongoDB database and perform data manipulations. From here on, the book will take you through integration with third-party tools to interact with web apps. You will see how to use controllers and view models to generate reusable code that will reduce development time. Toward the end, the book supplies tests to properly execute your code and take your skills to the next level with the most popular frameworks for developing web applications. By the end of the book, you will have a running web application developed with MongoDB, Node.js, and some of the most powerful and popular frameworks.
Table of Contents (19 chapters)
Title Page
About the Authors
About the Reviewer
Customer Feedback

A short introduction to MongoDB

As we discussed in the previous paragraph, MongoDB falls into the document store category of NoSQL databases. MongoDB is being actively developed by 10gen, which has been renamed to MongoDB Inc. MongoDB is open source and its source is available on various platforms, such as GitHub.

We will look at the following various features of MongoDB:

  • JSON-friendly database
  • Schema-less design
  • Various performance facets

JSON-friendly database

One of the most important reasons for the popularity of MongoDB is that it is a JSON-friendly database. This means that documents are stored and retrieved from MongoDB as JavaScript objects. Internally, this JSON data gets converted to BSON format while getting persisted to the system. So, this gives extreme flexibility, where we can use the same data format from client to server and eventually to the database.

A typical document (record) in a MongoDB collection (table) might look like the following code:

$ mongo 
> db.contacts.find({email: '[email protected]'}).pretty() 
   "email" : "[email protected]", 
   "phone" : "123-456-7890", 
   "gravatar" : "751e957d48e31841ff15d8fa0f1b0acf", 
   "_id" : ObjectId("52fad824392f58ac2452c992"), 
   "name" : { 
      "first" : "Jason", 
      "last" : "Krol" 
   "__v" : 0 

After examining the preceding output, we can see a key called _id. It is a MongoDB ID which must be encoded as a binary JSON objectID(BSON). If failed to encode, MongoDB won't be able to retrieve or update an object.

Schema-less design

Another important feature of MongoDB is its schema-less nature. With a relational database, you are required to define the exact structure of the data being stored ahead of time, which is termed as the schema. This means that you must have defined the exact number of columns, the length, and the data type for every field in a table, and that each field must always match that exact set of criteria. Mongo provides a flexible nature where the documents that you store into the database need not follow any schema unless the developer enforces it through the application level. This makes MongoDB a great fit for Agile-based development, as you could carry out modifications on the application schema on the fly.

Various performance facets

Other than the JavaScript-friendly nature, one other resemblance between MongoDB and Node.js is that MongoDB is also designed with highly concurrent applications with heavy read operations in mind.

MongoDB also introduces the concept of sharding, which makes it possible to scale the database horizontally as well as vertically. If the application owner needs to increase the database capabilities, they could add more machines into the stack. This is a cheaper option compared to investing in the RAM of a single machine, which will be the case in RDBMS solutions.

The process of Indexing created a list of values called index for a chosen field. These indexes are used to query larger chunks of data. Using indexes accelerates the data retrieval speed and performance. The MongoDB client provides various methods like ensureIndex to create an index only if one doesn't exist.

Additionally, MongoDB has various commands to allow aggregation of data, such as group, count, and return distinct values.

All the advantages that we discussed come with some impact on the consistency, as MongoDB does not strictly adhere to the RDBMS standards like ACID transactions. Also, if you end up creating a data model that might need too many JOIN operations, then MongoDB won't make a good fit as it is not designed with too many aggregations, even though the aggregations are possible via the MongoDB aggregation framework. MongoDB may or may not be the right solution for your application. You should truly weigh the pros and cons of each technology before making a decision to determine which technology is right for you.