Introduction
In earlier days, a single application had only a few thousand users. Today, more than millions of users are connected 24×7, throughout the year, with one application. Thus, businesses must have a good database that can handle massive volumes of data from the internet and multimedia. And most importantly, a simultaneous connection that can support more than a thousand users at one time. In this regard, the NoSQL database is one of the best options. And among all the NoSQL databases, MongoDB stands out as a highly sought-after and well-loved tool. In this article, we’ll understand what MongoDB is and its features and benefits. So, let’s get started!
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What is MongoDB?
MongoDB does not follow the principles of the Relational Data Base Management System (RDBMS), nor does it store data in tables like in a traditional database. Instead, it follows the concepts of collection and document databases. This document shares a lot of similarities with JSON objects. Unlike the traditional database, its value fields consist of other documents, arrays, and arrays of documents. In addition, it is regarded for its high performance, high availability, and automatic scaling. Because of this, it makes a perfect tool for building data warehouses. If you’re curious about how to install MongoDB in Ubuntu, then head to the MongoDB official site for an installation guide and install MongoDB in Ubuntu.
Also Read: Difference between SQL vs. NoSQL Database
What are the features of MongoDB?
MongoDB is an open-source and widely used NoSQL database today. It is different from other traditional databases. Now let’s take a closer look at its features down below:
Flexible Data Model: This data model allows users to store data from a complex array to an embedded document to key-value pairs and a simple document. These data are stored in BSON format.
High Performance: MongoDB is designed for quick and efficient data storage for vast volumes of data. Support for embedded data models significantly reduces I/O activity on databases. Likewise, index support promotes faster queries that contain keys from embedded documents and arrays.
Aggregation: This feature is similar to the SQL GroupBy clause. This function lets the user group data and get a single result or computed result. MongoDB provides three different types of aggregation: aggregation pipelines, map-reduce functions, and single-purpose aggregation methods.
CRUD Operation: Its rich query language support allows operations to be performed with a single command.
Replication Facility: This is nothing, but a group of replica sets of MongoDB servers that help maintain the same data set with automatic failover and data redundancy. As a result, it increases data availability.
Collection: A collection in MongoDB is like a schema-less database. Once collected, it can hold various documents that include different numbers of fields, content, and size.
Horizontal Scalability: MongoDB, at its core, provides horizontal functionality. And its sharding-nothing cluster architecture helps to distribute data across a cluster of machines.
What are the benefits of using MongoDB?
MongoDB is different from a relational database and does not have a schema design, which shows the relationship between the tables in the database. So instead of schema, MongoDB follows the concept of collections. Now, let’s take a closer look at its benefits:
No Schema Hassle: Since MongoDB does not use the schema, you don’t need to worry about designing the schema of the database while working with MongoDB.
Perfect for Small Businesses: If you want to start a small business or are a start-up company and are missing out on a database administrator, then MongoDB is low-maintenance and extremely beneficial for you.
Free and Fewer Server Costs: MongoDB is open source, so data storage and processing per gig are not at all costly. Plus, NoSQL database servers are always cheaper.
Single Object: If you need to deal with tons of unstructured data, the MongoDB structure of a single object makes everything clear. Generally, NoSQL databases don’t have storage limits.
User-friendly: MongoDB doesn’t have complex joins, nor does it follow the conversion or mapping of application objects to database objects. This makes it beginner friendly.
Query Ability: MongoDB supports dynamic queries and deep queries on documents using a document-based query language. This is as powerful as a SQL database.
Easy to Scale: MongoDB is easy to scale due to its sharding mechanism, where a large amount of data is divided into small pieces and then evenly distributed across various physical servers.
Agile Methodologies: While working with agile methodologies, relational databases fall short and slow down the process. Whereas MongoDB is more agile, its flexible approach makes it compatible with agile development.
Faster Access to Data: MongoDB uses internal memory to store the (windowed) working set; this, in turn, provides faster access to data. So, these are the features and benefits of MongoDB. If you’re a beginner and want to become a pro, access the comprehensive MongoDB tutorial and start learning.
Must Read: What are the various types of databases?
Conclusion
MongoDB ranks 5th on the DB Engine, making it one of the most popular NoSQL databases used widely today. MongoDB doesn’t follow the concept of tables and rows like in traditional relational databases; rather, it uses collections and documents. This document is nothing but the key-value pairs that make up a single piece of data in MongoDB. And collections, on the other hand, consist of documents and functions, which are similar to the tables of a traditional relational database. Also, it is well-known for its scalability, ease of use, and ability to run in a distributed and multi-platform environment.
Therefore, top companies, like Foursquare, SAP, and GitHub, are avid users of MongoDB. Additionally, its features and abilities make it a powerful tool for cloud computing. All in all, MongoDB offers quick and easy access to data. Its document-oriented NoSQL database architecture is perfect for high-volume data storage. And it also provides high data availability and instant and automatic data recovery. Using MongoDB, you can run performance-critical applications.
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Frequently Asked Questions
NoSQL is different from the traditional database in that it can efficiently handle unstructured data such as documents, emails, multimedia, and social media. It has very simple data and no fixed schema model. It uses the concept of identification keys, and data can be found based on the keys assigned. It is a flexible, scalable, and reliable solution for storing high-volume data. Some of its notable features are its flexible schema, horizontal scalability, ease of use, and fast queries.
MongoDB doesn’t have the concept of joins, which makes it difficult to join stored documents. This can be done manually by writing code, but this process is more time-consuming and slows down performance. Sometimes MongoDB can suffer heavily from duplicate data; this also makes it hard to manage data efficiently.
MongoDB technical support teams are experts who are always ready to offer help with any issues you may encounter. Apart from this, MongoDB is easy to scale, its database is highly flexible, and it offers encryption features and a secure database management system.
MongoDB is better for unstructured data; it is more suitable for projects that deal with extensive data, whereas SQL works with structured data with schemas. So, if you’re working on complex questions, then SQL is the preferred choice.
MongoDB is a non-relational database with no predefined schema and no support for table relationships.
MongoDB is written in C++. It is more compatible with Python, Java, and C.
By using MongoDB Cloud Atlas, users don’t have to pay expensive costs; it comes with disaster recovery and robust security; and lastly, it is highly flexible and scalable.
It is a platform that allows users to write, test, and execute queries directly in the browser.
Some of the important interview questions are related to MongoDB projection, MongoDB comparison with Cassandra, the structure of MongoDB documents, and indexing in MongoDB.
