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No SQL v Sql: what should you use for your business?

Remember when there were times when you used to jot down important stuff that

you chances were that you probably remembered to do that important but there are

much better odds that you forgot about that task and have just gotten about with

your day.

Certainly if you compare now big businesses used to store their important

information you can just tell that there was a problem here that needed addressing.

SQL was invented by IBM researchers in the 1970s. SQL is a programming language

that is used to interface with databases. It understands and analyzes database tables

that include data fields. For example, take a large organization that has to store a lot

of data. The organization collects and stores information from various departments.

All the gathered information is organized and stored in a database, but it has to be

valuable and accessible that's where SQL comes in.

You may ask by looking at the above paragraph that what is a database concept? A

database is basically a brick of data which stores information in the form of tables.

SQL is a powerful language that can help manage and modify large volumes of data.

Some important SQL commands include: SELECT, DELETE, CREATE DATABASE,


popular language for accessing databases as it is compatible with all databases.

Advantages of learning SQL

1) Universal Language: One of the methods that crosses over into many different

areas is SQL. Working with SQL involves speaking computer language. This

motivates you to advance into programming using other languages, such as

C++, JavaScript, Python, and others. These are all priceless skills that are still in

demand.All you need to succeed with a programming language is a vision of

the industry you want to work in. You can improve your skills to specialise as a

programmer, developer, manager, and more during the time you spend

learning SQL. Although it seems corny, there are virtually no restrictions on

what you can accomplish with SQL.

2) Easy to Learn: SQL is an open-source programming language, so it has a large

developer community. Many SQL and MySQL-related topics are consistently

posted on StackOverflow. SQL is easier to learn than other programming

languages such as C++. Furthermore, many popular SQL databases (MySQL,

MariaDB, and Postgres) are open-source.

3) Able to manage millions of data: Traditional spreadsheets can only handle

small-to-medium-sized data sets, so we'll need an alternative solution to

handle such massive data sets. Fortunately, this is a field where SQL shines:

whether it's 1,000 records or 100 million, SQL is completely capable of handling

data pools of virtually any size.

Did your spreadsheet crash because there were thousands of columns of

data? Relational databases are designed to store data in millions of rows. SQL

allows you to perform operations on this massive amount of data without fear

of crashing. Microsoft Excel is a fantastic tool, but it was not designed to

handle tasks on millions of rows at once. Relational databases are designed for

such large tasks, and SQL is the language used to create them.

A lot of people might think looking at the title of the blog and also might think from

the name of the programming language, NoSQL that it was developed in order to

address the drawbacks of SQL but that isn’t the case here, The language was

developed in relation to SQL.

With the rise of social media, messaging apps and various other social media sites it

was time to develop a programming language to help us manage with this huge

inlow of data. Yes, SQL came first. It’s used to communicate with relational databases.

Relational databases store data in a very organized, but also rigid way. NoSQL,

earning it’s name by being “not only SQL” makes it easier to store all different types

of data together. It’s used for its flexibility and therefore speed and scalability in

managing large volumes of data.

The ability to store large amounts of data in a flexible manner speeds up the

development of NoSQL. You may: Create a database without first developing a detailed database model. Store all types of data without defining the type of data ahead of time. Add new data types without rewriting the schema. NoSQL works well with high-speed, agile development teams. It enables rapid changes to the database schema as the scope and requirements evolve.

Again, this does not imply that SQL is slow. If your data is highly structured and you

expect little change, NoSQL is probably unnecessary. SQL is mature and supported

by a strong technical community, so your engineers will not encounter problems

that they cannot solve. Using NoSQL Standardization is also lacking in NoSQL databases. For example, MongoDB and Cassandra DB are both good NoSQL databases for a new NoSQL engineer to learn.

However, if an engineer first learns MongoDB, they may struggle with Cassandra DB

due to the lack of standards in NoSQL.

One of the main issue with SQL is scalability, we are in a constant need for scaling up,

By scaling up we mean adding extra hardware, RAM, processing power in order to

increase capacity. With SQL we’re limited because we will inevitably max out on

capacity and scaling up is expensive. Scaling out with SQL is possible, but requires

extensive effort (partitioning, sharding, clustering, etc.) and cost.

NoSQL engines are built to scale out and take advantage of cloud computing. When

we scale out or horizontally, we add resources to a single node (a computer or

server). We can run a single database on multiple nodes. We can easily add and

remove nodes when we scale out (or back in). As a result, NoSQL is an excellent

choice for the cloud. You will be maximising the cloud's scalability benefits because it

can scale out. You can run SQL on Azure, for example, but your ability to scale will be


When to use NoSQL instead of SQL?

1) You are constantly adding new features, functions and data types

2) Changing a data model is clunky and requires more time doing the same in

NoSQL. A lot of time is invested designing the data model because changes

will impact all or most of the layers in the application.

3) In NoSQL, we are working with a highly flexible schema design or no

predefined schema.

4) You are not concerned with data consistency, and complete data integrity is

not your primary goal.

5) You have a lot of data, a variety of data types, and your data requirements will

only grow over time.

When to use SQL instead of NoSQL?

1) You are working with complex queries and other related stuff

2) If you are not working with a lot of databases and functions SQL is the best to

use. NoSQL will seem overwhelming if not a lot of databases and functions are


3) You need to ensure ACID compliance. ACID stands for Atomicity, Consistency,

Isolation, and Durability. These words describe how transactions interact with

a database.

Cloud-Based SQL

Now you know when and how to use both these very useful languages according to

your business needs. With the rise of Cloud Computing, SQL is also available as a

cloud service provided by Google Clouds in order to have an alternative to the local

versions of MySQL, and other SQL-based data servers.

Combining them with all of the APIs, the machine learning algorithms, and deep

learning algorithms available as a service to the users, Cloud Computing acts as the

perfect catalyst.

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