NOSQL vs SQL. Key differences and when to choose each

Nowadays there is a rising tendency to use NoSQL databases.

In this article we want to clear up the differences between both database types (SQL and No-SQL) and on what occasions should we choose one over the other for your project.

What are NoSQL databases?

Before going further, before talking about relational and non relational databases, we need to explain a key definition. One definition that is sometimes missunderstood due to its own terms.

Do you know what NoSQL means?

It is not a literal acronym (NO using SQL). Instead, No SQL means Not Only SQL. Important to keep in mind.

Difference between SQL and NoSQL

There is a fundamental difference between both database types. And it is explained as simply as:

1. SQL means that we use relational databases.
2. No SQL means that we use NON relational databases.

In other words, relational and non relational database model is what characterizes one or another. But it does not mean that No-SQL databases do not use SQL, but we will explain it later.

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Relational vs non relational database

Essential concepts clarified, come with mee to see what are the advantages and disadvantages of each of the models.

This will help you to have a global vision of its utilities and, therefore, will help you make a decision on which one to use in your specific case.

1. Relational databases (SQL database)

Explained as simple as possible, a relational database is based on storing and accessing data that is related to each other.

SQL databases have a straight, direct and intuitive way of showing us the data they store in tables.

Within those tables, each row will represent a record that will have a unique identifier (known as key). Columns will include attributes of those keys, normally with unique values (which allows us to create those relationships between the data of the entire database). Thus giving this type of BDD its name.

Relational database advantages

• Its use is more adapted and the profiles that know it are mainstream, and therefore less expensive.
• Due to the amount of time that they’ve been on the market, these tools have better support, product suites and add-ons to manage these databases.
• The atomicity of operations on the database. This means that on these databases either the entire operation is done or it’s not done at all, using the famous ‘rollback’ technique.
• The data must comply with integrity requirements both in data type and compatibility.

Disadvantages in relational databases

• The atomicity of the operations plays a crucial part in the database’s performance.
• Scalability, even though it’s usually tested in productive environments, it’s usually lower than NoSQL databases.

2. Non relational databases (NoSQL database)

Contrary to the previous ones, this type of data storage does not use such simple structures (tables), nor is its data stored in the form of records or fields.

That doesn’t mean they don’t use SQL language.

Its very name, as we explained before, does not mean NOT to use SQL, but rather it means not always to use SQL. They rely on it, but only as a means of support, not as their primary query tool.

Let´s talk about the NoSQL pros and cons:

Advantages of a NoSQL database

• Scalability and its decentralized style. It supports distributed structures.
• They’re usually much more open and flexible as databases. They allow adapting to the needs of a project in a much easier way than entity related models.
• Changes in the schemes can be done without having to stop the database.
• Horizontal scaling: they’re capable of growing in device number, instead of having to reside in one large device.
• They can be run on low-resource devices.
• Query optimization on databases designed for large amounts of data.

Disadvantages of NoSQL databases

• Not all NoSQL databases contemplate the atomicity of instructions and the integrity of the data. They withstand what’s know as eventual consistence.
• Compatibility issues with SQL instructions. New databases use their own characteristics in the query language and they’re not yet 100% compatible with the SQL used in relational databases. Support for work query issues in a NoSQL database is more complicated.
• Lack of standarization. There are many NoSQL databases and there is still no standard like the ones that exist in relational databases. An uncertain future is predicted for these databases.
• Cross-platform support. There are still many improvements to be made on some systems so that they can run on non-Linux operating systems.
• Poor usability. They usually have not-really-useful management tools or console access.

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When to use SQL vs NoSQL

This series of rules will guide you on whether you need a NoSQL vs relational database (SQL).

• When the data must be consisten without leaving room for error when using a relational database. SQL.
• When our budget won’t allow large devices and must be put into lower performance devices. NoSQL.
• When the datastructures we manage are variable. NoSQL.
• For analyzing large quantities of data in read mode only. NoSQL.
• Event capture and processing. NoSQL
• Online stores with complex intelligence engines. NoSQL

It is very important to insist that, although it seems that at the moment you should migrate your databases to NoSQL, you have to take into account if the characteristics of your database really require a NoSQL or relational database before making this decision. .

Here we leave you this video of Google itself talking about the two types of databases. It is an old video in date, but whose content is still totally valid:

If you want to know more…

We hope you find this article comparing the NOSQL vs SQL model useful.

If you need to know more about non-relational databases or NoSQL databases, we invite you to enter our No-SQL databases guide.

And if you want to broaden your horizons and make sure your databases all work as they should: