SQL Full Form vs Python: What’s the Difference?

Python and SQL are two popular languages across professions, with each offering a unique set of advantages, limitations, and built-in features to improve your workflow. Depending on your use cases and professional needs, you can decide which programming language features will benefit you most. By carefully considering each language and its applications, you can improve your motivation and commit time to learning a new language effectively. 

What is SQL full form?

The full form of SQL is structured query language. SQL specialises in relational database management and manipulation. If you are unfamiliar with relational databases, they are a collection of data tables, each linking to others through keys. 

Let’s say you have a table of information about your customers. In this table, each column has a different identifier (key), such as customer names, regions, and purchases. These identifiers would link to separate tables for a relationship database, including more detailed information within each category. SQL provides a specialised syntax for adding, querying, updating, and deleting database records, making it a great choice for database management tasks.

SQL was originally named SEQUEL, which stood for Structured English Query Language. Developers created this software at IBM to retrieve information from the organisation’s database using relational algebra and calculus algorithms [1]. Over time, its application has expanded to various purposes, including composing scripts, managing databases, and responding to queries.

What is SQL used for?

You can use SQL to interact with your databases and perform various operations. For example, you can use SQL to insert, update, delete, and query your data to prepare it for analysis. In essence, you write commands in SQL to tell it how you would like to alter your database. 

SQL excels in handling structured data, where you have well-defined data entities. As a professional, you might use this software to manage customer databases, sales transactions, and inventory management systems.

Who uses SQL?

Professionals across industries use SQL, especially those in database administration, data analysis, and back-end development roles. Because developers continually design and update databases, SQL knowledge can significantly improve their ability to effectively manage large data tables and relational databases. 

Data analysts and data scientists also commonly use SQL, leveraging its functions to clean and analyse their data sets, gaining insight into underlying structures, and providing strategic insights to their organisations. As a data analyst, you might choose SQL because you can integrate it easily with other programming languages, such as Java, PHP, and CSS. As a data scientist, you might use this combination of languages when building dynamic web pages, using each programming language to facilitate a different aspect of your design. 

Almost every industry collects and manages data, so you’ll likely see SQL used in various settings. Within finance, banks use SQL to record and manage transactions, adding layers of security and regulations for their customers. The music and social media industries also use SQL, using its proficiency with big data to manage personal information, activity, and recommendations continually.   

Pros and cons of SQL 

While SQL has many advantages, you should also consider the limitations of this language before deciding if it is the right choice for you. Several pros and cons to consider include the following.

Pros

• Doesn't rely on writing extensive code: SQL allows you to manage and query databases without requiring lengthy programming scripts. 

• Interactive database: SQL provides an interactive approach to database management, providing immediate feedback.

• Simple to learn the basics: SQL's syntax is intuitive and user-friendly, making it approachable for beginners.

• Applicable in various industries: The versatile functions make it a valuable skill across numerous sectors, including finance, health care, technology, retail, and more.

• High job demand: Proficiency in SQL is an in-demand skill employers seek.

• Compatible with other languages: SQL integrates easily with programming languages, such as Python, Java, and C#.

Cons

• Complex interface: The interface may have a learning curve, meaning you will need to dedicate time to learn it effectively.

• Potentially high operating costs: Depending on the database system in use, the costs associated with licensing, maintenance, and scaling can be an obstacle.

• Proprietary versions: Certain SQL database systems are proprietary. This means companies own them and can charge licensing fees. 

• Incomplete control of the database: SQL operates within predefined structures and permissions, which means you might not have full control over the database management and operations, depending on your permission level. 

What is Python?

Python is an object-oriented programming language known for its user-friendly syntax and comprehensive packages. Python is also a general-purpose programming language, meaning it’s highly adaptable to different purposes and not designed for a specific function. 

Python was first introduced in 1991 by Guido van Rossum, who developed it to allow programmers to write effective code with fewer commands than needed in other languages [2]. Since its distribution, Python has become one of the most popular programming languages globally, utilised by industry giants like Spotify, Netflix, and Google. 

What is Python used for?

Python is a general language, and its user-friendly interface and library system make it suitable for applications across different domains. Not only does Python offer extensive packages, but it is also the base of several development tools, frameworks, and platforms that you can use for advanced technical tasks. For example, you might see Python used for:

• Web and internet development (Django and Pyramid frameworks)

• Scientific and numeric computing (SciPy and pandas packages)

• Software development (SCons and Buildbot construction tools)

• Business applications (Odoo and Tryton platforms)

Who uses Python?

Python is growing in popularity amongst professionals in India and is the third most popular programming language developers use globally in 2023 [3]. Python’s general-application design makes it popular for professionals within many different industries. Software developers often use Python to build software and develop web applications, while data scientists and analysts rely on Python for data exploration, machine learning models, and complex data analyses. 

Professionals in academia and research use scientific computing packages within Python for computational research and academic projects. Professionals of all types can use Python to write scripts that automate processes, which enhances efficiency, work quality, and delivery speed.

Pros and cons of Python 

Deciding whether Python is the right language for you to invest time into learning should be a conscious decision after weighing the pros and cons. Python is a high-level language that requires dedicated effort to learn, but committing to this journey can enhance your skill set, improve your workflow, and open new professional opportunities.

Pros:

• High demand: Python is one of the most popular programming languages globally, leading to a high demand for Python skills in the job market.

• Good for machine learning and AI: Python's use of libraries designed for artificial intelligence applications (TensorFlow, sci-kit) makes it a natural fit for machine learning professionals.

• Extensive libraries: Python has an extensive collection of libraries, covering everything from web development to data cleaning and data analysis.

• Embeddable within other software: Python can be embedded into applications written in other languages, enhancing their functionality.

• Free and open source: You can modify your source code to fit your needs, making it easy to apply Python to different projects.

Cons:

• Not preferred for mobile app development: If mobile applications are your primary interest, you may want to look into other software options.

• Slower than C or Java: As an interpreted language, Python tends to run slower than compiled languages like C or Java.

• Takes up memory: Python consumes more memory than other low-level languages, which can be a limitation for memory-intensive applications.

How to decide whether to use SQL or Python

When choosing between SQL and Python, focus your decision on the specific needs of your project, the nature of your data, and the tasks you aim to accomplish. SQL is specifically designed to excel at these tasks if your primary focus is on database operations, such as querying, managing, or manipulating data within relational databases. You should also think about whether your tasks require direct interaction with databases. If this is the case, SQL may offer superior performance and efficiency compared to Python, as many databases are optimised for SQL operations. 

Meanwhile, Python is a versatile tool for broad applications, including complex data processing, analysis, and predictive modelling. Python has extensive libraries, making it a language you can apply across different professional tasks. For example, you can utilise different Python libraries for tasks such as automation, integration with web applications, writing scripts, and machine learning applications, making it suitable for projects that extend well beyond database management.

How to build a foundation in SQL or Python

Whether you decide Python or SQL is the right choice, having a strategy to build a strong foundation in either language can help you develop your skills effectively and organised.

Take classes

Enrolling in structured classes can provide a comprehensive introduction to SQL or Python. You can choose between many styles and levels of courses online, including those offered by educational institutions and online learning platforms. 

Use online tutorials

Online tutorials offer the flexibility to learn at your own pace. They can be a great way to supplement formal education or classes or provide step-by-step guides to your specific questions.

Practice

Practice is important to mastering any programming language. Start by working on small projects or problems that interest you. Regular practice can help you remember concepts and learn new problem-solving strategies. 

Join a community

Joining a community of fellow learners and professionals can significantly enhance your learning journey. Look around online to find support groups that relate to your interests.

Getting started with Coursera

Developing a strong foundation in either SQL or Python—or both—can open up numerous career opportunities and enhance your analytical capabilities. While SQL excels with relational database tasks, Python has many applications across data analysis, web development, and machine learning applications. To explore each language more, consider taking courses on the Coursera learning platform, such as Introduction to Structured Query Language (SQL) or Data Analysis with Python.