One of the first large-scale issue of web app architecture you will have to make is: Do I need a SQL or NoSQL database? Now, it is extremely important to be immersed in the difference as a full-stack developer as you will have a direct effect on the performance, flexibility, scalability and maintainability of your projects.
In my upcoming content, I am going to deconstruct the difference between SQL and NoSQL, the advantages and disadvantages of both, and in which context one can be used over another based on actual cases.
What is SQL?
Relational databases simply referred to as SQL databases are decades old. They keep information in tables, like spreadsheets, and each row holds a record, and a column holds a piece of information (such as name, email, or created_at). It is a rigid structure, you have to carry in advance how your information will be structured with a schema.
The reliability of SQL databases is exceptionally high when it concerns the application where data relationships and consistency are important, i.e., e-commerce tools, financial systems, or inventory tools.
Here’s a quick look at what a typical SQL table might look like:
This schema tells the database exactly what kind of data to expect. If you try to insert something that doesn’t match, it’ll throw an error, which is actually a good thing when you need data integrity.
What is NoSQL?
At the opposite end of the scale, we have NoSQL but even though the title implies that there is no structure or no query language, it is not correct. It only implies that it is not SQL only.
NoSQL databases are structured to be non-relational implying that they are not based on hard table structures. They instead store data in more versatile formats, such as JSON documents, key-value pairs, graphs or wide-column stores. If we have a user in MongoDB it would be a document like this:
As you can see, there is no predetermined schema. It is possible to add or delete fields without a modification of a table structure. Such flexibility predestines NoSQL as a favorable solution to quickly changing projects, particularly when you do not know precisely what your data model will be.
So, When Should You Use SQL?
Choose SQL when your application is dependent on a properly structured, relational data. When it comes to creating an e-commerce system, you will most probably end up having users, orders, products, and reviews connected in a myriad of ways. It is beautiful when performed by a relational database (such as PostgreSQL or MySQL) as it keeps your data consistent and closes to accurate.
And, in case you require to execute complicated queries such as retrieving all orders of the customers who purchased a specific product within the past 30 days, you should use SQL instead.
Another use case is on financial applications. There is no chance you can afford losing or corrupting data because you missed a transaction. SQL databases are ACID compliant and therefore ensure data integrity by maintaining atomicity, consistency, isolation and durability.
When is NoSQL the Better Choice?
Assume, you are creating a chat. Your data is evolving seriously fast, you do not require intense connections among the entities, and you do not require settling on solid structure. NoSQL is at its best here.
Let us take an example where users are able to create a dynamic content, such as a post with a tag, mention, or reaction - a document-based NoSQL database, such as MongoDB, enables you to store all this material in a single document without complex join tables or migration scripts.
Horizontal scaling is also carried out via NoSQL as well. When millions of users in different parts of the world will be using your application, NoSQL databases (such as Cassandra or DynamoDB) will make it simpler to scale out data across numerous servers.
Real-World Example: Building a Blog Platform
Here’s a simple example from a full-stack dev perspective. Let’s say you’re building a blog platform.
You might use a SQL database for things like:
- User authentication
- Roles and permissions
- Comments that require joins with users and posts
Meanwhile, you could use NoSQL to store:
- The actual blog post content, which may have a flexible structure (title, content blocks, tags, SEO metadata, etc.)
- Real-time analytics (e.g., page views per second)
- Cached user profiles using something like Redis
Sometimes, the best solution is a hybrid, using SQL where structure matters, and NoSQL where flexibility or performance is key.