SQL vs NoSQL: Complete Comparison

In the current context, Big Data is becoming more and more widespread and is becoming part of all IT ecosystems. In this field, or in computer development in general, the choice of the database management system to use is crucial. For the latter, two options are possible, namely SQL and NoSQL.

In this article, we will perform a comprehensive comparison of these two systems so that you can choose the one that best suits your project.

SQL vs. NoSQL: definition

the NoSQL is the more recent of the two, since it has only been popularized since the advent of Big Data, that is to say for only about ten years. However, its invention dates back to the 1960s. For some, NoSQL means the absence or rather the reversal of SQL. For others, it refers to Not Only SQL, that is, another way of using or combining SQL with another system.

In reality, it is simply a non-relational database system. What this suggests is that there is no structure or imposed formats when retrieving and storing data in this type of system.

Indeed, several data formats are accepted in a NoSQL database such as documents, images, graphics, etc. This provides more flexibility and scalability to the system requiring huge storage volume. This is also the reason why giants such as Google, Twitter, Facebook and Amazon have adopted this DBMS.

SQL or Structured Query Language, on the other hand, is by far the oldest database management system, as it has been around and has been around for over 40 years now. Unlike NoSQL, it is a database management system and at the same time a so-called relational language.

It is based on a tabular structure, that is, everything is organized in rows and columns. Based on a DBMS called System R, it has been used since its creation and until now on several types of projects ranging from a website to any software. Its ease, flexibility and structure have made it quickly adopted by developers.

SQL vs. NoSQL: use cases

In theory, NoSQL is used when, in your project, you plan to store and process data:

  • Having a high volume, that is to say that the amount of data you want to handle is relatively high;
  • With various formats, you may be planning to store images, documents, videos, etc. ;
  • At higher speed, you want to get the results of your queries as fast as possible;
  • Which will be used for artificial intelligence or machine learning.

Here are some examples of use cases in everyday life:

  • In the field of finance, namely in banking, payment systems, etc. where the existence of several data formats to be processed is necessary. This type of company must interact with their database management systems in an efficient way in order to avoid possible fraud and thus guarantee the security of its customers;
  • In the field of online commerce where several products must appear on the site in a few moments. The inventory management of its products also requires the use of NoSQL;
  • If an application requires real-time interaction, i.e. it must provide high availability and respond to user requests immediately.

On the other hand, you use SQL DBMS if you are building customer-facing applications. If you need a backend system where you can perform joins between multiple tables or multiple types of information, this is the one for you. It’s sturdy enough to be portable, so if that’s important to you and your project needs, then you should go with SQL.

The real cases of use are numerous, due to its age and its reliability during its lifetime. It can therefore be found in many sites such as blogs, e-commerce sites, web applications, desktop software, some machine learning and financial applications and many more.

SQL vs. NoSQL: structure

NoSQL is, as we stated in its definition, is a non-relational database management system. This means that the same structures are not necessarily used for the different data formats that can be stored there. Nevertheless, we can identify four main types of NoSQL databases, namely:

  • Document-oriented databases in which semi-structured objects are stored. These objects may have no relationship or even be completely different. This type of NoSQL database can also contain nested documents or even key/value or key/array pairs;
  • Key/value oriented databases in which data is accessed through keys that have their respective values. In this type of database, the key must be absolutely unique;
  • Graph-oriented databases that are used to store graph-like data, as the name suggests. In reality, it is the type of structure used to connect objects. This is, for example, where we store the data networks that are present on social networks;
  • Column-oriented databases that store objects or data online. This is very handy for transporting huge amounts of data stored online like relational database management systems.

For SQL, as it is a relational database, there is a pre-established structure that must be respected. SQL databases are always made up of tables made up of rows and columns. A table can have constraints as well as dependencies on other tables which are also called joins.

SQL vs. NoSQL: Differences

Although these two systems can store data efficiently, they have several aspects that differentiate them. Let’s look at all these points one by one:

  • First of all, as we saw in the previous section, their structures are not at all the same. Indeed, that of SQL is fixed and pre-established while that of NoSQL is dynamic, scalable and adaptable according to the type of data to be stored;
  • For data access, SQL language uses queries for CRUD and NoSQL uses APIs;
  • The accepted formats is limited in SQL while it is more varied in NoSQL;
  • SQL databases are usually stored on a single server. Some constraints may arise in relation to this. For example, to extend the database, the storage spaces of the server must be increased. Availability is also reduced because of this architecture.

On the NoSQL side, we adopt a distributed architecture, that is, when we need to extend the database, we just need to add another server, another machine or another cluster node . Thanks to this architecture, the databases offer higher availability and higher scalability;

  • The speed of the two systems will depend on the structure and the volume of data to be processed;
  • SQL is easy to learn, the syntax remains the same no matter what tool you are going to use. NoSQL is more technical and requires a certain skill level to use it well;
  • All NoSQL development platforms are open source. For SQL, you can find open sources as well as paid software;
  • If you want to use SQL, you have the choice between MySQL, SQL Server, PostgreSQL, Access, SQLite or Oracle DB databases. And if you want to use NoSQL, there is for example MongoDB, Cassandra, MariaDB, Redis, ArangoDB or even Neo4j.

Now you have the comparison between these two database management systems. If you have to make a choice, you must first think about your needs and the overall architecture that your project may have and the goal you want to achieve. As soon as you have all this information, take a look at what each of these systems offers and choose the one that best suits your expectations.

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SQL vs NoSQL: Complete Comparison

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