SQL and NoSQL What's The Difference

As a programmer, you have different options when it comes to database management. As the most common database language, SQL is what you will find used in many systems. However, NoSQL can be good for certain applications.

This article is going to discuss the differences, and the times when it is more advantageous to use one over the other.

What is SQL?

SQL stands for Structured Language Query. It is essentially a language for managing databases. With SQL programming, you perform a variety a database management tasks like inserting, deleting, updating, and searching. Essentially, it is a system that makes the data usable.

SQL has been the standard language for database management for a long time, and you have a variety of SQL systems that can be used. While the different SQL systems perform many of the same functions, and have similar features, they tend to have their own extensions and custom syntaxes, so many of them will be incompatible in some ways.

What is NoSQL?

NoSQL is an alternative system for database management and the acronym stands for Not only SQL. Whereas SQL works on relational database concepts, NoSQL is non-relational. NoSQL is a newer system, but that does not necessarily mean that it is better. It is just better for specific applications.

Just like with SQL, you have a range of different NoSQL systems that you can use. In the same way, many of the systems are similar and operate using a common structure. That said, these systems will also come with various features that may not be interchangeable.

As a further point, SQL and NoSQL are not exclusive to each other. Some SQL developers have started adopting features of NoSQL, and you will find NoSQL systems that follow certain features of SQL. In addition to that, the two systems can work together for certain applications.

What are the Differences?

Before you can figure out which of the two is right for a specific situation, you have to know the differences between the two. As I mentioned above, SQL manages data in a relational format and SQL is non-relational or distributed.

One of the key differences is that SQL manages data in tables. You have different rows for different data sets and columns that define the values for the information. With NoSQL, data is managed in key-pair sets, graph databases, wide-column sets, or documents.

Another key difference between SQL and NoSQL is the way in which these different systems scale. SQL systems scale vertically, meaning that you have to increase the power of the hardware to scale up. With NoSQL, the system is horizontally scalable, meaning that the system is scaled by increasing servers for the database.

As a final difference, SQL is a system that requires a schema for the data to be useable. Before you can add data, you have to define the tables and fields. Under a NoSQL framework, the system does not need the predefined schema. This allows you to add data without the requirement of defining various elements related to the data.

When Should You Use Each?

While both are used to perform similar functions, they each perform better for different types of applications. In general, SQL is going to be better for databases where most of the records will have the same properties and for applications that require strict data integrity.

If your system is going to use a lot of data that comes from different sources, or if you have complex database functions that will draw on various types of data, NoSQL can be better. To perform the same types of functions with SQL, you would have to construct multiple tables for the different types of data. Then, to use the information together, you would have to write complex join queries to fetch the data from the various tables.

When it comes to finding the right database language, there is a lot to consider. Here, you have a basic breakdown of these two systems, and an idea of when each will work better. That said, this is a complex question that requires a deep knowledge of the ways that these systems work and the answer depends upon the specific database requirements of the application.