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Why SQL Is the Perfect Database Language

Which programming language should you learn if you want to work with databases? We’ll explain why SQL is the top choice!

Learning a database language can be an incredibly valuable skill in today's data-driven world. But with so many options out there, it can be difficult to know where to start. In this article, we'll make a compelling case for why SQL is the ideal choice for anyone looking to dive into the world of databases. Whether you're a seasoned developer or a curious beginner, you'll see why SQL is the way to go.

Why Are Databases Important?

Databases are essential parts of many contemporary applications – including e-commerce platforms, content management systems, social media platforms, etc.. Databases are crucial to the operation of these systems because they allow for the safe, orderly, and efficient storage, access, and manipulation of substantial amounts of data.

Applications can quickly and accurately update the data in databases with guaranteed data integrity and consistency. This is thanks to data regulations that are built into the database.. This is crucial for applications that rely on data-driven operations and processes, such as social networks, real-time analytics, online shops, and online marketplaces.

To work with any database, we need a language that lets us communicate with it. This will let us access the data, analyze it, and update or delete it when necessary. The good news is that you are in the right place to learn a straightforward and popular database language! Our comprehensive SQL from A to Z track will take you from SQL newbie to advanced SQL user, providing you with everything you need to work with databases professionally.

Why Is Choosing the Right Database Language Essential?

Choosing the appropriate database language is crucial because it will determine how effectively you can manage, access, and store data. You  need a language that offers the features and capabilities required to satisfy today’s security- and speed-conscious data demands. These include:

1. Improved Efficiency

By enabling quicker data storage, retrieval, and processing, the right database language can increase efficiency.

2. Reduced Costs

Long-term financial savings can also be achieved by employing the proper language. In addition to savings from lower storage costs, the right database language can lower the cost of maintenance and upgrades.

3. Enhanced Security

The language you decide to use for your database can also affect how secure your data is. Protecting your data from malicious activity can be accomplished by choosing a robust and secure language.

4. Expanded Compatibility

You can make sure that your data is available to and usable by anyone who needs it by choosing a database language that is compatible with other programs and technological advancements.

5. Improved Performance

The performance of your database can also be enhanced with the right language. It can ensure that your database is performing at its best and that queries are optimized for speed and accuracy.

Why SQL Is the Language of Relational Databases

For more than 50 years, SQL has been the preferred language for relational databases. This is because of its straightforward and effective syntax, adaptable data types, and capacity for sophisticated queries. If you're curious to learn more, read our article What Is an SQL Database?.

SQL's high degree of portability allows it to be used across various database systems and lets us easily transfer data between systems. Since SQL has been around for a while, many developers are familiar with it; thus, the SQL community is large.

SQL the Perfect Database Language

There are currently no signs of SQL losing its place as the go-to language for relational databases. Since SQL is well suited to handling distributed data, its popularity is actually rising as more organizations adopt Cloud-based and distributed data solutions. In addition, new add-ons and tools are being created to enhance the functionality and power of SQL. Check out our article The Future of SQL for more information on where SQL is heading.

Do Other Database Languages Exist?

There are other database languages out there – although none are as widely used or as popular as SQL. Each language has its pros and cons, and which language is the “best” depends on the application and the context in which it is used. Some examples include Neo4j's Cypher (which is used for graph data) and NoSQL. The most popular examples of NoSQL are MongoDB and Cassandra.

What Is NoSQL?

NoSQL, which stands for “Not Only SQL”, is a database language that does not involve SQL syntax. NoSQL uses non-relational databases, which are a type of database that doesn't follow the conventional relational database structure.

Instead, non-relational databases are structured as a flat file. This file usually contains data in the form of a single table, a collection of documents, graphs, or key-value pairs. In contrast to a relational database, a non-relational database does not impose a rigid structure on the data being stored.

Where Is NoSQL Used?

NoSQL offers a way to store and retrieve data that is not modeled using the tabular relationships found in relational databases. It is used for handling large amounts of unstructured and semi-structured data, such as in Big Data and real-time web applications.

Why Isn’t NoSQL Standard?

Unlike SQL, NoSQL is not based on a single, unified language. It is a collection of various database types that serve various functions and keep data in various formats. There is no single NoSQL database standard because each type of NoSQL database has its own unique set of features and capabilities. As you can imagine, this makes learning NoSQL much more challenging.

Development of NoSQL vs. SQL

SQL has been around longer than NoSQL. The relational database era was launched in the 1970s by Edward Frank Codd at IBM Research.

The original purpose of the language was to allow users to access data stored in IBM’s System R relational database system. Since then, SQL has been adapted by a wide range of database systems and applications, becoming the standard language for data access and modification. Want to learn more about SQL's history? Check out The History of SQL - How It All Began for more information.

SQL the Perfect Database Language

NoSQL came around later, with the term ‘NoSQL’ first appearing in the late 2000s. Modern web-scale applications' needs led to the development of these databases.

SQL vs. NoSQL: Choosing a Database Language

When it comes to choosing the best database language, SQL comes out on top over NoSQL for several reasons. Let’s explore them in more detail.

1. Simplicity and Usability

The SQL language is uncomplicated, approachable, and easy to learn. Don’t believe us?  See our article Is SQL Difficult to Learn? to prove it! Using a database's declarative syntax, you can specify what you want to get from it without worrying about the specifics of how it will be done.

Beginners can use SQL because of its simplicity, but the language can still handle complex queries. If you’re a beginner and want to start your SQL journey, check out our SQL Basics course, where you can get hands-on practice with SQL without having to download a thing!

NoSQL databases are built using a variety of languages, making it more challenging to comprehend and learn.

2. Scalability and Flexibility

With a wide range of database systems, SQL is a very flexible language. Whether you're working with a tiny local database or a sizable distributed system, SQL can scale to meet your needs. Furthermore, SQL is a widely accepted standard language, which makes switching between different systems easier.

The fact that NoSQL databases frequently lack the flexibility and power of SQL when it comes to querying structured data is one drawback of NoSQL queries in comparison to SQL queries. NoSQL databases may not have the same support for complex joins, subqueries, and other advanced features as SQL because they are typically designed to handle unstructured or semi-structured data.

Additionally, some consistency and data integrity features that are crucial for particular kinds of applications may be forgone because NoSQL databases are frequently optimized for high scalability and performance. This may make it more challenging to guarantee that data in a distributed NoSQL database is accurate and consistent across all nodes.

Since NoSQL databases are typically designed to handle large amounts of unstructured or semi-structured data, they may not have the same support for complex joins, subqueries, and other advanced features that are available in SQL. Therefore, in comparison to SQL they are considered less flexible.

3. Data Security and Integrity

By ensuring that data is stored in a structured and trustworthy manner, the relational model of SQL lowers the likelihood of data errors and inconsistent data. Because it supports a wide range of security features – including encryption, access control, and audit trails – SQL gives database designers options for storing sensitive data.

The level of security features that a SQL database offers are typically not present in NoSQL databases. Data stored in a NoSQL database is more susceptible to malicious attacks; NoSQL databases do not provide the same level of authentication, authorization, or encryption as conventional SQL databases.

4. Reliability

Given that they are made to handle sophisticated queries and transactions, SQL databases are designed to be dependable. Since they have been in use for so long, SQL databases have been examined and found to be trustworthy.

On the other hand, NoSQL databases are more recent and have not undergone as much testing. Because they lack the stability and dependability of conventional relational databases, NoSQL databases are typically regarded as being less reliable than SQL databases. They frequently lack the ability to enforce data constraints and tend to have less robust data integrity, which can result in inconsistent data and security flaws.

5. Performance and Optimization

SQL is designed to run database queries quickly and effectively by streamlining the process of doing so. The SQL query optimization engine is able to analyze complex queries and determine the best method for retrieving the required data. Additionally, SQL gives you the option to create indexes and perform other optimizations to further improve query performance.

Want to Learn the Best Database Language? Learn SQL!

Overall, SQL is the best database language to learn because it is robust and flexible. SQL allows you to efficiently and quickly execute complex queries. Fortunately, learning and using SQL are both very simple. So what are you waiting for? Enroll in one of our courses today, and read our article on 5 Tips for Learning SQL for Beginners for advice on how to get your SQL journey started!