App Development: What Are the Main Differences Between NoSQL & SQL Databases

App development has become so prominent today because of how interconnected everything is through digital. Desktop, web, mobile, and cloud-based applications permeate various industries. Recreational and business avenues alike rely on apps to run, with the market only continuing to grow as the years go by.

App Development What Are the Main Differences Between NoSQL & SQL Databases

With over seven million apps across iOS and Android alone, there are no signs of things slowing down as thousands more get added every month. The amount of engagement and revenue for apps keeps development in demand. TikTok, the top grossing app of 2022, generated $2 billion revenue. Even major gaming mobile apps that experienced a decline saw staggering revenue, with PUBG Mobile getting $1.12 billion.

With so much data being created, stored, and modified, using a proper database is essential for these applications to survive. The right one will depend on the actual use case, so it’s important to know the main differences between NoSQL vs.SQL databases.

What is an SQL Database?

An SQL, or Structured Query Language, database is a popular kind of relational database management system (RDBMS) that was first developed in the 1970s by IBM. Its primary purpose is to serve data banks to store and manage data in a structured way.

You’ll commonly see data organized into predefined columns and data types within a tabular structure. This makes establishing relationships between tables and keys more efficient. Essentially, SQL lets you define and implement a database and then manage it afterward. So, if you need to modify, collect, or enter data, you would be able to do so within the database management system.

Any data engineer in 2023 will know the role of SQL databases in a modern roadmap for data science, machine learning, and web and app development. SQL is fundamental, along with normalization and ACID transactions. From there, developers must consider horizontal vs. vertical scaling and dimensional modeling. Popular relational databases to work with are MySQL, PostgreSQL, MariaDB, and Amazon Aurora.

Main Use Cases for SQL

The dynamic nature of SQL databases makes it a common choice for healthcare, finance, and marketing. Data analytics is a core component of decision-making in businesses, so SQL derives its insights from databases that collect essential information on a real-time basis.

It’s also worth noting that MySQL is one of the most basic AI tools that developers need to learn when creating applications for Web2. This same skill set can then be carried over to Web3 development. As web applications constantly handle data requests, frameworks need to be used for various functions like querying, code groupings, and app sharing without the need for source code to be manually shared each time.

What is a NoSQL Database?

A No SQL database is flexible. Unlike SQL, it does not use a relational data model, which means you primarily scale horizontally and can make iterations more quickly. This is because it has a flexible schema that allows for fast queries and changes. It has become popular with developers because of it makes mapping and coding much easier.

Aside from simplifying the process for developers (with less code needed in the first place), it also allows for fewer bugs and shortened development time. This makes it a viable resource for quick deployment and constant updates. Although SQL databases still lead in terms of the most popular database management systems in 2023, the top NoSQL options in the market are MongoDB and Redis.

The former makes use of disk data storage, while the latter uses in-memory storage. What has made MongoDB so popular is its constant updates, adding support for new libraries and must-haves like ACID transactions in shared clusters.

Main Use Cases for NoSQL

Because of its framework, you can commonly see modern NoSQL used in catalog management, IoT, messaging, and content management systems. It allows for solid customization while handling different types of data easily. It’s very scalable, meaning you can adjust to demand at high speed and “cheaper” implementation.

As big data continues to grow at a rapid pace, NoSQL becomes the solution for developers to have a more reasonable workflow. Hence, huge platforms like Facebook, Netflix, and Google have made the switch to NoSQL.

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