Mongodb Tutorial: All you Need to know
Updated on Oct 06, 2022 | 7 min read | 5.7k views
Share:
For working professionals
For fresh graduates
More
Updated on Oct 06, 2022 | 7 min read | 5.7k views
Share:
Table of Contents
As of 2021, a survey conducted on software developers shows that MongoDB is the second-most wanted database skill, just after PostgreSQL. MongoDB is an in-demand skill among developers, and the best way to learn it is through a MongoDB tutorial.
MongoDB is a document-oriented database used to build scalable Internet applications. Due to its schema approach of database designing, MongoDB is especially popular with developers and software professionals working with agile methodologies. MongoDB is ideal for building dynamic and modern big data applications with its flexible schema design offerings. With MongoDB, you can store, manage, and retrieve data and experience seamless application building without application downtime.
This MongoDB tutorial for beginners will walk you through the fundamentals of MongoDB, including a brief MongoDB query tutorial.
Get data science certification from the World’s top Universities. Learn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career.
MongoDB is an open-source documented-oriented database. It falls under the NoSQL database category because, unlike traditional databases, MongoDB does not use tables and rows for data storage and retrieval. Instead, each record in a MongoDB database is a binary representation of the data (BSON) that applications can retrieve in a JSON format. Below is an example of a simple JSON document format:
Next, in this MongoDB tutorial for beginners, we’ll look at some of the fundamental concepts of the NoSQL database.
Collection
MongoDB documents are a collection equivalent to a table in RDBMS (Relational Database Management System). A single database comprises a collection and does not enforce any schema. In addition, a collection includes documents with different fields with related purposes.
Database
A database is a container for collections, with each database receiving its own set of files on the file system. A MongoDB server can typically store multiple databases.
Document
A MongoDB is the basic building block of data and consists of field and value pairs. While the value of a field is typically BSON data type, field names are strings. A field in MongoDB is what a column is in a relational database. Documents are grouped into a collection, and documents within a collection may have different fields. Also, BSON documents may have multiple fields with the same name.
Our learners also read: Learn Python Online for Free
_id
The _id field represents a unique value and is mandatory in every MongoDB document. It is a 12 bytes hexadecimal number that serves as a document’s primary key. Thus, MongoDB automatically provides the unique _id for every document even if you create a new document lacking the _id field.
Below is an example of a MongoDB document with values of different types:
MongoDB addresses several limitations of relational databases and other NoSQL solutions to ensure scalability and flexibility. In this section of the MongoDB tutorial, we will discuss some of the technical features of MongoDB.
Indexing
Indexing is a crucial part of databases and, if done right, enhances performance and search speed. Improper indexing often leads to accessibility issues. It is possible to index any field or key in a MongoDB document. The extensive indices and features on MongoDB support even the most complicated access patterns to datasets. Moreover, you can create MongoDB indices as per dynamic and real-time query patterns and requirements.
Ad hoc query support
Ad hoc queries are temporary commands whose values are variable-dependent. Thus, the variable in question decides the result every time an ad hoc query is executed. Ad hoc queries become significant when numerous variables come into the picture. MongoDB offers ad hoc query support, allowing developers to make real-time updates in ad hoc queries. Optimizing ad hoc in this way improves performance and enables scalability.
Sharding
Sharding means splitting large datasets across multiple collections or “shards.” It allows better execution since working with massive datasets can cause unexpected problems. MongoDB allows for horizontal scalability with the sharding feature. In horizontal scaling, the collection of distributed shards makes it easier to handle a dynamic application and ensures zero downtime. In MongoDB, instances called mongos manage all the operations in the sharding environment.
Replication
Replication means distributing data across multiple servers for backup and disaster recovery. It helps avoid potential failures such as hardware malfunctions, service interruptions, or service crashes that usually result when data is kept in a single database. MongoDB uses replica sets to achieve replication – a primary server accepts write operations and replicates them across secondary servers.
Load balancing
Optimal and efficient load balancing is critical for database management, and MongoDB ensures large-scale load balancing through features like sharding and replication. MongoDB simultaneously manages multiple read and write requests for the same data through locking protocols and concurrency control. The platform achieves all this without any external load balancer.
MongoDB is one of the most sought-after databases among developers due to the ease and convenience of data storage, management, and retrieval. At the same time, it is simple to learn and use and can be used to create robust applications using most programming languages. Let’s look at some of the advantages of MongoDB that make it so popular.
MongoDB is a general-purpose database with use cases spanning different businesses and industries, including finances, telecommunications, gaming, retail, and healthcare. This section of the MongoDB tutorial looks at some of the specific use cases of MongoDB.
MongoDB Query is a way to retrieve data from the MongoDB database. It is similar to SQL queries in SQL databases and simplifies getting the data from the database. Moreover, query operations in MongoDB also allow using conditions or criteria for fetching specific information from the database. The find() method is used to perform query operations in MongoDB, and its basic syntax is:
db.collection_name.find()
MongoDB is beneficial for working with vast sets of distributed data due to its schema approach’s flexibility and scalability. Most importantly, MongoDB has official driver support for some of the most widely used programming languages, including Java, C, C++, C#, Python, PHP, Pearl, and more. Google, Adobe, AstraZeneca, Forbes, Toyota, Thermo Fisher Scientific, KPMG, Barclays, and eBay are a few prominent companies using MongoDB.
If you are looking to enhance your knowledge of databases or aiming for a data science career, the Professional Certificate Program in Data Science and Business Analytics from University of Maryland, a Top US university is the perfect way to get started. Here’s what the 9-months online program offers:
Get Free Consultation
By submitting, I accept the T&C and
Privacy Policy
Start Your Career in Data Science Today
Top Resources