SQL vs NoSQL Databases : A Noob Approach

SQL Databases, as its name suggests, use Structured Query Language or better known as SQL. With the help of SQL, defining and manipulating data is done within databases. The majority of modern databases are administrated with the help of SQL. On the one hand, SQL is one of the most potent tools or languages when it comes to the subject of databases. SQL makes itself very useful, especially with topics like complex queries. The versatility and wide usage are highlighted.

On the other hand, SQLs restrictive nature is disturbing. SQL has this unique predefined schema that forces data to follow the same structure. The up-front preparation required for this process quite a deal.

“The most significant difference between these concepts is that SQL database is relational and contains foreign keys. On the contrary, the NoSql database is irreversible and so does not define the relationships.

At first glance, SQL may seem to be outweighing the benefits of NoSql, but it may not be true automatically. NoSql does not offer any security features to us, but more it reads and writes data. Therefore, it is used for BigData applications, where terabyte data are expected. NoSql is also an ideal choice if we need to implement a complex full-text search engine that takes similar words, mimicry or other grammar rules into account. NoSql too solves the problem, when we do not know database schematics first. Conversely, we need to address the data consistency on an application side, and that is the downside. Another drawback is that the NoSql database does not support transactional processing.” (Roman and Michal Kvet,2019)

It may look like no big deal, whether it is SQL based or nonSQL based. Nevertheless, the fact that data is the most crucial asset of a company can not be just thrown away out of the window. Data is what forms the source for the analysis, evaluation and decision making. Sophisticated storage structures and access principles are the main and primitive requirements for Complex data management. Moreover, as Michal Kevt’s quotation explains, it makes a considerable difference based on the method used to manage the Database.

Truth be told, in the modern world, SQL seems to be a bit outdated. And NoSQL solutions are at the top as of now. For example, Google’s Firebase platform was a standalone platform founded in 2011 and until Google bought it in 2014 and converted it into one of their services. As of 2021, it is Google’s flagship offering for app development. The most exciting thing about Firebase is that Google has embedded an AI system with a high precession, making Firebase way user-friendly than SQL based DB management systems. However, that is not exactly a win-win situation for Firebase tho. There are pros and cons of both Firebase and SQL.

When it comes to architecture, Firebase stores and syncs data in real-time (a real-time document store), while MySQL is a relational database management system that happens to be open source as well. Data handling features of Firebase is specially designed to handle an extensive data set, while MySQL is designed to handle complex data sets. Language support is a crucial factor in database management. Otherwise, it would be disastrous trying to connect the database to the front end design. MySQL supports more programming languages than Firebase, including Ada, C++, Python, and many others. Price is a factor that depends on person to person, Firebase has a free version and a paid version, and MySQL is both free and open-source. Since Firebase supports Android, iOS, JavaScript, RESTful HTTP APIs, and MySQL supports ADO, JDBC, ODBC APIs, it can be said that both of them have their own ways.


However, considering the new technology trends, it is safe to assume a Database management system based on a cloud service would fit well in modern-day internet culture. That is where Firebase comes in real handy. Firebase’s ML Kit and other heavy tools are run with ease within the cloud. If this process is expected to project with SQL, it should go through Python and R, making a big scenery requiring high performing resources and more time. So the author’s recommendation here is that new Database management systems should be cloud-based, considering the improvements the society has achieved in all of these years. Since all over these years, the phrase Larger Dataset has been redefined several times. It is a fair point to move on Tasks involving large datasets from local Database management systems to a cloud database management system.

Considering the vast amount of mobile devices out there, it is seemingly a wise and futuristic decision made by the tech giant Google. Allowing data to sync with Android, iOS, and JavaScript SDKs is a giant leap for a Database management system, which clearly lacks in MySQL. In order to exist in the mobile world, which is growing way faster than the old computer world, it is a must to sync with mobile devices. The author is likely to recommend emerging SQL databases to interact more and more with mobile devices. When the word mobile is used, it may sound like it is all about phones and tablets, but frankly, it is not. Here, mobile refers to IoT. IoT is becoming the most significant thing in technology history. Lack of proper synchronization would be a disruption to the rapid advancement of mobile technology.

“The server used for Android apps are Oracle SQL, Microsoft

SQL Server, and MySQL which are connected to the server

with PHP files. Then Firebase came into existence for

Android apps that use JSON for storing data. The other

servers use a table (rows and columns) format for storing data.

Firebase is NoSQL based. There are very few cloud-based

server available which are similar to Firebase, like:

AWS Mobile Hub- It is an integrated console that helps to create,

build, test, and monitor the mobile apps that leverage AWS


CloudKit- It is an Apple framework that helps to save data

and store assets but similar to iOS only.

Parse Server- It was released by Facebook to replicate

the functionality of Parse which is an open-source server. This is

no longer in existence as Facebook shut down this project.” (Chunnu and Pritam, 2018)

In conclusion, Firebase and MySQL are two databases that arrive at the same destination but take different routes to get there. As a cloud-based NoSQL database, Firebase handles large data sets effectively. As an open-source RDMS, MySQL is more than capable of taming complex data. Ultimately, MySQL is the cheaper of the two and offers more language support.

“The presented analysis of databases used by the most popular social network sites (Facebook, YouTube, Twitter, Instagram and LinkedIn) showed that most of them use combination of different databases, both relational and NoSQL, in order to resolve diverse needs and requirements of their users. The main motif behind NoSQL database development is finding solutions for Big Data challenges (volume, velocity and variety of data). NoSQL databases answered to those challenges through distributed, cluster-oriented, horizontally scalable and lately tunable consistency features. But when data querying and analyzing is in question, NoSQL databases with use of different programming languages and APIs turned out to be inadequate solution, opposed to standardized SQL (Structured Query Language) used by relational databases. In meantime, the largest database management vendors (Oracle, Microsoft, IBM) realized that NoSQL databases bring some innovative and good solutions to the problems they had been facing for years (Big Data, high availability, distribution). They innovated and expanded their relational databases and thus brought them closer to NoSQL databases. On the other hand, NoSQL database vendors are developing support for SQL in order to make data analysis easier for their users. The future will prove is the bridging the gap between relational and NoSQL databases the path that can lead to new database evolution. However, that new databases should be able to provide support for different and often opposite users requirements by enabling combinations of both approaches through tunable and configurable capabilities that will give the users the opportunity to use databases on the way that best suits their needs.” (Gašpar and Mabić, 2017)

In brief, if the goal is to handle a complex data set with ease, then the option is explicit. MySQL is the most suitable option in such a case scenario. Otherwise, in need of handling a large dataset or Big data, it is safe to go with a NoSQL method such as Firebase. However, it entirely depends on the task user is up to. And also, not to mention that a user familiar with MySQL for a long time will not find NoSQL alternatives friendlier or more accessible. As above mentioned, both SQL and NoSQL database systems have their pros and cons, and it is up to the users to choose which to use.

References :

  • Gašpar and Mabić, (2017). NoSQL Databases as Social Networks Storage Systems
  • Chunnu and Pritam, (2018). Application of Firebase in Android App Development-A Study
  • Roman and Michal Kvet,(2019). Comparison of query performance in relational a non-relation databases

Wandering the internet with a great interest in technology.