Databases are becoming increasingly widespread, and practically every company now uses them for a variety of purposes. Simultaneously, database technologies have advanced over time and now offer a wide range of capabilities. A Relational Database, whether Oracle, SQL Server, or DB2, has been the dominating back end of commercial systems since the 1980s.
With Big Data being the most important thing in IT since the Internet, developers all around the world are working on applications that can support a wider range of data formats. As Relational Databases generally don’t cater to the growing Unstructured Data, NoSQL databases are becoming a new favourite among businesses in recent years.
In comparison to Traditional Relational Databases, proponents of NoSQL platforms claim that they allow easier scalability and better performance. This category includes Open-Source solutions like Cassandra, MongoDB, and Redis, which excel at storing Unstructured Data.
In this article, you shall learn the basic introduction to MongoDB and building MongoDB REST API.
Table of Contents
Introduction to MongoDB
MongoDB is a well-known NoSQL Database that was created by MongoDB Inc. It’s a cross-platform Document-Oriented Database application that stores data in JSON-like documents with optional schemas.
MongoDB makes use of BSON and MQL, a SQL-like language. BSON (or Binary JSON) is a binary serialization of JSON that allows for the representation of non-JSON data types. BSON supports data types such as Long, Floating-Point, and Date that aren’t supported by standard JSON. BSON, for example, supports a ‘Date’ data type that would usually be saved as a string type in JSON.
Understanding the Architecture of MongoDB
Here are the key terminologies and components associated with MongoDB:
- _id: The “_id” field in a MongoDB Document represents a unique value. The _id field acts as the primary key for the document. MongoDB will automatically construct an _id field if you create a new document without one, as this field is an integral part of every MongoDB Document.
- Collection: This is a set of MongoDB Documents that have been grouped. A collection is the equivalent of a table in any other Relational Database Management System (RDMS), such as Oracle or MS SQL. A collection is a subset of a database. Collections do not impose any kind of structure.
- Cursor: A cursor is a pointer to a query’s result set. Clients can retrieve results by iterating through a cursor.
- Database: A database is a container for collections, similar to how a Relational Database Management System (RDMS) is a container for tables.
- Document: A document is a record in a MongoDB collection. The document consists of field names and values.
- Field: A name-value pair in a document is called a field.
Key Features of MongoDB
- Query Support: Ad-hoc and document-based queries are supported by MongoDB.
- Adjustable Schema: You may alter the database’s schema on the fly, which cuts down on the time it takes to add new features or repair current issues.
- Data Storage: You can store almost any type of data, whether it’s structured, partially structured, or polymorphic.
- GridFS: A file of any size can be stored without cluttering your stack. GridFS breaks files into smaller chunks and saves them as individual documents.
- Replication: It has functionality for Master-Slave replication. MongoDB maintains multiple copies of data using native applications. One of Replica Set’s benefits is that it has a self-healing shard, which prevents database downtime.
- Indexing: Without indexing, a database would have to sift through every document in a collection to find the ones that match the query, which would be inefficient. As a result, indexing is required for efficient searching, and MongoDB employs it to analyze large volumes of data quickly.
- MapReduce: For data processing, MongoDB supports MapReduce. Large amounts of data are consolidated into usable aggregated results using MapReduce.
- MQL: MongoDB employs the MongoDB Query Language (MQL), which is a powerful and expressive query language. It includes CRUD (Create, Read, Update, Delete) operations, data aggregation, text search, and geospatial searches.
- Support for Multiple Servers: MongoDB can run on numerous servers. This redundancy can protect the system against hardware failure.
- Security: For sensitive data, MongoDB supports security capabilities such as authentication, access control (user, role-based access control), and encryption (TLS/SSL). The security features available are also determined by the pricing tier.
- Sharding: When compared to typical Relational Database choices, MongoDB provides remarkable scalability. It offers horizontal scaling (sharding), which allows you to add more Instances with more capacity as needed.
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Introduction to REST API
API (Application Programming Interface) refers to a set of subroutines and protocols that allow two components to communicate with one another. REST (Representational State Transfer) is an architectural approach based on HTTP that provides a set of limitations (Hypertext Transfer Protocol). As a result, if an API’s architecture is based on REST, it is said to be RESTful.
Generally, HTTP RESTful APIs include:
- HTTP Method: GET, PUT, DELETE, PATCH, and POST
- Base URI: For ex, http://adrianmejia.com
- URL Path: For ex, /blog/2014/10/01/creating-a-restful-api-tutorial-with-nodejs-and-mongodb/
- Media Type: For ex, Html, JSON, XML, Microformats, Atom, and Images
Key Constraints of REST Architecture
1) Uniform Interface
For decoupling a client from a server, REST API adheres to offering a uniform interface that allows for independent application development without having the application’s services, models, or actions tightly linked to the API layer. The uniform interface allows the client to communicate with the server in a single language, regardless of the backend architecture of either. This design concept simplifies the overall system architecture and improves communication visibility while also preventing self or multiple interfaces within an API.
Identification of resources, resource management through representations, self-descriptive communications, and hypermedia as the engine of the application state, are the four interface constraints that constitute REST.
2) Client-Server Separation
This design approach is founded on the notion that client and server should be separated and allowed to grow independently of one another. The communication between them is limited to requests initiated by the client and responses sent to the client as a reaction to a request. Users may enhance manageability and scalability across many platforms by simplifying server components since user interface issues are separated from data storage problems.
REST APIs are stateless, which implies that the server keeps no information on the user who uses the API. The requests sent from a client to a server will include all of the necessary information for the server to comprehend the client’s requests. This can be part of the URL, query-string arguments, content, headers, API key, access token, user ID, and so on. It also permits lower memory use and scalability of the user’s application.
The architecture of a REST API consists of various layers that work together to form a hierarchy that aids in the creation of a more scalable and adaptable application. It is possible to put critical and more susceptible elements of server architecture behind a firewall, prohibiting direct interaction with them by the client, by using a layered system with a proxy, or providing a single point of access. It also balances loads and provides shared caches to help with scalability.
5) Code on Demand
This is an optional constraint as an API can be RESTful even if it does not provide code on demand. It enables the transmission of code or applets for usage within the application via the API. This reduces the number of features that must be pre-implemented, which benefits clients.
Creating a MongoDB REST API
Selecting the appropriate database for your REST API is crucial, and based on current trends, MongoDB is one of the most popular databases for web applications. MongoDB REST API is simple to set up and allows you to store and retrieve documents, making it great for Unstructured Data.
Using Express JS as the backend web server with MongoDB as the document store is a common way of implementing the MongoDB REST API strategy. This approach conveniently links MongoDB’s Document Model to the JSON-based REST API payloads. You can use Express to build a backend middle tier that runs on Node.js and exposes REST API routes to your application. The Node.js Driver also connects the Express.js server to the MongoDB Atlas cluster. For this, you will need to install Node.js by following the appropriate guidelines mentioned here.
You will also need to sign up for MongoDB Atlas, which is a Cloud Database as a service. MongoDB Atlas offers a free sandbox environment that will allow you to focus on building your MongoDB REST API. Further, you will require a Code Editor like Visual Studio Code or Sublime Text.
It’s worth noting that one of the first things you can do to ensure a successful start of MongoDB REST API is to prepare your workspace. The first step is to verify that your MongoDB instance is operational. Once you’ve confirmed that the MongoDB instance is up and running, you may use the MongoDB client to connect to the server and inspect your collection, data, and run queries, among other things.
You’ll need to make an application folder for the app to live in. To start the application, you’ll need to generate a package.json file that contains all of the node application’s metadata. The file instructs npm to install the package dependencies as well as the scripts you will write to run the application and you can get started with MongoDB REST API.
Step 1: Setting up the Project
If you have Node.js installed, you can run the following command to start the application from the command line:
The above command will create a package.json file.
Step 2: Installing Application Dependencies
For MongoDB REST API to run, you need a file that will serve as the application’s command centre. When you ask npm to run your application, it will initially run this file. This file can include object instances of both your modules and third-party modules installed from the npm directory.
You created a file named app.js, which will be the application’s main entry point, and installed a few dependencies that are required to run your application using the commands above.
These are the dependencies:
- Express: A framework for Node.js.
- MongoDB: The MongoDB team has supplied an official module to let your Node.js application communicate with MongoDB.
- Body-parser: It will handle request bodies with Express.
Step 3: Run Code
Here, you are importing the dependencies you downloaded before. Use the Express object to initialize the express framework, which will utilize the express framework to start the server and run your application on a certain port, as well as configure the body-parser, which is a middleware that parses incoming chunks of data.
Step 4: Testing Application for MongoDB REST API
Step 5: Establishing Connection with MongoDB REST API
For this, you will need the MongoDB REST API connection string. Choose Clusters from the Atlas dashboard, then the Overview page, and then the Connect button. You will need to add the string to the app.js file and perform the following code adjustments.
Step 6: Build MongoDB REST API Endpoint
Next, you will need to establish and query endpoints for the data. To add the data, we’ll need to construct an endpoint. To app.js, add the following code:
Step 7: Testing the MongoDB REST API
You’ll see the personnel record for John Doe added into the MongoDB database of ‘accounting_department.’
Your MongoDB REST API is ready to use
This article showed how to create a MongoDB REST API. It also gave you an in-depth understanding of MongoDB’s features and REST architecture‘s limits, so you can better comprehend and apply MongoDB REST API where it’s needed.
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