SQL Myths Debunked: 6 Lies About SQL You Need to Stop Believing

SQL has been around for decades, yet misunderstandings about it continue to circulate. Some people think it's outdated or not suited for today’s data challenges. But are these claims really true? Read on to explore the common myths about SQL and separate fact from fiction.

There are many misconceptions about SQL (Structured Query Language). With all the buzz around new technologies, some believe SQL has become irrelevant and incapable of handling today's data needs—but that couldn't be further from the truth.

In this post, we'll debunk common myths about SQL, clarify its capabilities, and demonstrate why it's still a vital skill in today's tech world.

Myth #1: SQL is Becoming Obsolete

Some think SQL is going away with the rise of new technology. There’s a notion that SQL is old and will be replaced by something newer.

SQL is not obsolete. It’s still one of the most used and popular database languages. Companies in almost every industry still use SQL for data management and analysis. In fact, SQL has evolved over time and is still essential for small and big applications.

According to the StackOverflow 2024 Developer Survey, SQL continues to be one of the most in-demand skills for data professionals, with a significant percentage of respondents listing it as a key technology used in their daily work.

From startups to large corporations, SQL remains the backbone of many data management systems. For more insights on current database trends, check out: Database Trends: Is SQL Still the King?

But SQL’s relevance isn’t the only thing that’s often misunderstood. Let’s talk about how approachable it really is.

Myth #2: SQL is Too Complex For Beginners

Many people are intimidated by the idea of learning SQL. It often looks like a complex language, full of technical terms that seem hard to understand.

SQL is actually quite approachable. It was designed to make it easy to interact with databases using simple, readable commands like

Here is an example of a simple query to show just how easy it is:

SELECT first_name, last_name FROM customers WHERE city = 'New York';

This query retrieves the first and last names of customers who live in New York. The SELECT command is used to specify the columns we want (to fetch data from tables), and the WHERE clause filters the data based on the condition provided. It's a straightforward way to pull data from a database.

Start with simple queries and gradually increase the complexity. Practice using free tools or courses, such as those offered by LearnSQL.com. For a structured learning path, consider the SQL Basics course. Hands-on practice is the key to learning SQL effectively.

Even with basic SQL knowledge, you can do a lot, such as pulling data from a customer database or generating simple reports. These practical applications make SQL a valuable skill, even for beginners.

Myth #3: SQL is Only For Relational Databases

People think SQL is only used with traditional databases, such as MySQL or PostgreSQL.

While it’s true that SQL started with relational databases, it has evolved over time. Today, SQL can be used across different platforms, including cloud databases and hybrid environments. SQL is versatile and adaptable for many use cases.

Examples of SQL's versatility:

• Cloud databases: SQL is widely used in cloud environments like Amazon RDS and Google BigQuery, allowing users to query data stored in the cloud.
• Data lakes: SQL is used with data lakes, such as AWS Lake Formation, to manage large volumes of unstructured and structured data.
• Hybrid environments: SQL is also used in hybrid setups where on-premise data interacts with cloud-hosted data, providing seamless data querying capabilities.

SQL is part of modern data stacks. It works well with data lakes, cloud services and even with tools used for data analytics. That’s why SQL remains relevant, no matter the environment.

Myth #4: Modern Tools Make SQL Obsolete

Some think modern data tools, such as BI (Business Intelligence) tools, have made SQL unnecessary.

Many BI tools rely heavily on SQL under the hood. Tools like Power BI, Tableau and Looker use SQL to connect to databases and pull the data for the visualizations.

Power BI uses SQL queries to connect to databases and allows users to write SQL directly into their data models. This means that users who know SQL can actually create more complex and precise analyses. Check out this article to learn more about SQL and Power BI.

Tableau’s data connection process often relies on SQL queries. Users can leverage SQL to filter, join, or transform data before it even reaches the visualization stage.

Looker’s LookML, which is used to model data, often translates into SQL queries in the background to perform data analysis. To learn more about data analysis in Looker, check out this article.

Knowing SQL makes you more powerful with these tools because you can write custom queries to get exactly what you need. It amplifies the capability of  BI tools by giving you more control over the data and more customization options for dashboards and reports. For example, you can perform complex joins or aggregations using SQL—operations that are not always possible through the drag-and-drop interfaces of BI tools.

SQL is not obsolete; it’s the silent engine behind many modern data tools to give users the flexibility and control they need to get the most out of their data.

Myth #5: SQL Can’t Scale For Big Data

There’s a myth that SQL databases can’t scale for large datasets. Many think SQL can’t handle the complexity or size of big data.

SQL can scale, thanks to modern techniques like sharding, partitioning, and distributed SQL databases. With the right setup, SQL databases can handle millions of transactions and large volumes of data.

Take Facebook for example. Facebook uses MySQL—a popular SQL database—to manage massive amounts of user data. They use sharding to scale.

If you want to improve scalability, consider indexing your tables properly and using partitioning. This helps your SQL database perform better, even with larger datasets.

Myth #6: SQL Isn’t Useful For Non-Technical Roles

This myth is common among business professionals and product managers, who think SQL is only for developers or data analysts.

SQL can be very useful for non-technical roles. Imagine being able to pull your own data without waiting for the IT team. With basic SQL knowledge, product managers, marketers, sales managers, and business analysts can get direct insights from data, speed up decision-making, and increase productivity.

With SQL, non-technical users can make data-driven decisions on their own. They can run queries that answer specific questions about their business, gain understanding of customer behavior, track product performance, or evaluate the success of a marketing campaign. By being able to interact with the data themselves, they can get the information they need without having to wait for someone else to generate a report.

A marketer can use SQL to analyze campaign data, find out which channels are performing best or which audience segments are most responsive. They can adjust their strategy in real-time for maximum impact. A product manager can use SQL to track feature usage, see how users are interacting with the product, and identify areas for improvement. A sales manager can use SQL to segment customers based on sales performance so they can focus on high-value clients or target specific demographics more effectively.

These are just a few examples of how those in non-technical roles can use SQL to gain insights and make better decisions. By knowing just a little bit of SQL, non-technical professionals can become more self-sufficient and proactive with data and make faster and more informed decisions.

Conclusion

SQL is still powerful, versatile, and relevant. It continues to be a key tool for managing, querying, and analyzing data across various industries. Whether you are a beginner or a professional, SQL has something to offer—and the myths about its limitations are often far from the truth.

If you're interested in learning more, consider checking out the SQL From A to Z track. This comprehensive learning path covers everything you need to know about SQL, from the basics to advanced topics, through a series of hands-on courses.

You'll learn how to write effective queries, manipulate data, and understand complex SQL concepts in an approachable way. The courses are designed to be interactive, allowing you to practice what you learn and get real-time feedback.

Plus, you can try it out for free to see if it’s a good fit for you. Start mastering SQL today and take control of your data analysis skills!