SQL vs NoSQL Databases: what should you choose – and when?

Database technology has been around for quite some time now and most people are well familiar with it. However, in this article, we are going to examine the essence of two major database types: SQL and NoSQL. Also, we are going to compare them and give suggestions which one to use depending on your needs.

SQL

To begin with, SQL is an abbreviation for “structured query language”. That’s the language, which most commonly we are using for requesting information from a traditional database. Another vastly used term is “relational database”(RDBMS). It originates from the mid-1970s when an IBM researcher created the version SEQUEL (Structured English Query Language).

Core Differences:

The core difference between SQL and NoSQL is how they are built, the type of information they store and the mechanics of storing it.

SQL is the more rigid, structured means to do it. Imagine a phonebook. It consists of two or more tables with columns and rows. Each row represents an entry and each column sorts a very specific type of information (like name, address or phone number). The Schema is the relationship between tables and field types. Identifying the schema first is a crucial step, before adding any information to the database.

When is SQL is better?

In order for a relational database to be effective, the input of information needs to be consistent and structured. Having a well-configured schema will help you avoid data redundancy and tables running out of sync. Crucial for a handful of businesses especially the ones that handle financial transactions on a daily basis.
One additional reason SQL databases remain ever so popular with developers is that they fit naturally in venerable software stacks, including LAMP and Ruby-based stacks. These databases are vastly popular, therefore well understood. Which means you can have easily available support(given that something doesn’t go according to plan).

NoSQL

SQL databases might be a perfect suite for companies with constant and unchanging data. For instance, banks or supermarkets where transactions are continuous and follow the same pattern. Data in modern businesses (Big Data is the motivator here) is predominantly unstructured and of large volumes. Using a relational database in such cases is a sure formula for failure. Therefore, a non- relational database is the more logical choice. Offering great flexibility and the ability to store massive amounts of data. A good way to explain a non-relational database is storing data of the same type in folders (imagine a WordPress blog, where every folder will store data for the blog post: social likes, photos, text, metrics, links and more). Here are two popular scenarios.

When is NoSQL better?

• If your data requirements are not clear from the very beginning of your business and you are dealing with immense amounts of data. Then you simply will not have the advantage of building a relational database with a clearly configured schema. How does a NoSQL database work? Unlike relational databases, non- relational databases are document-oriented. Unstructured data (such as articles, photos, social media likes, videos or content within a blog post) is saved in a single document. That document is afterwards easily accessible, expandable, updatable and so on. On top of that, it doesn’t require categorization into fields as SQL does.

• Scalability of the databases is a key concern when choosing which one to implement. SQL databases are vertically scalable, one can increase the load on a single server by increasing the computing power (CPU, RAM or SSD). Whereas, NoSQL databases are horizontally scalable, meaning they can handle more traffic by sharing or adding an additional server. (Imagine it as adding more floors to a building versus adding more buildings in the neighbourhood). Ultimately, non-relational databases expand easily and with low-cost commodity hardware in mind. Which makes them the prefered option for large ever-changing data sets.
• Another major advantage of the NoSQL databases is particularly to app developers: ease of access. SQL databases have a troublesome relationship with applications, written in an object-oriented programming language (like Java, PHP, and Python). NoSQL databases are able to avoid the problem using APIs. They allow software engineers to execute queries without having to learn SQL or understand the underlying architecture of their database system.

So which one works best for you?

At the end of the day, there is no one superior database system. It all comes down to the needs of your business. If the data you store has a predefined structure and set schemas, you are better off using a relational database. For example, applications that require multi-row transactions such as accounting systems or inventory monitoring systems. On the other hand, NoSQL databases are a good choice if you are dealing with rapid growth or databases with no clear schema definitions. Example of such cases are mobile applications, where data schemas are continuously changing and it’s near to impossible to design one that lasts.