Here’s When You Should Use SQL Vs NoSQL
A definitive guide to the popular question of when to use SQL or NoSQL for your database.
Myclients often ask me, why isn’t SQL the best approach here?
Often they want to know why we even need NoSQL if SQL can get it all done.
This article is my formal answer to these questions.
It’ll help you with a definitive answer on when you want to use SQL vs NoSQL and the logic behind the decision on a technical level.
Use this as a guide every time you find yourself choosing the best database for your application.
Understanding your access patterns
It all starts with your data access patterns.
What are the access patterns your application needs?
Does your application need to query related data often or more rarely?
Is your data naturally relational? Or does it have a mix of some related data but a lot of dispersed data?
The core of your decision should be driven by your access patterns.
If, for example, the majority of your queries need to fetch data from a single table and/or return single items mostly, SQL may not be a good choice.
If your access patterns are on the flip side of this, SQL may be a great choice.
Below, I’ll list some great use cases that fit the SQL model and some use cases where NoSQL will be a better fit for your data to reside in.
When to choose SQL
SQL excels at letting you query relationships in your data. Essentially, it helps you join multiple related tables so your query results fetch data that is related, together.
Let’s take an e-commerce platform database as an example.
In SQL, you typically have a Products table, a Customers table, and an Orders table.
From a data perspective, these tables are all connected.
Customers place orders and orders contain products.
With a customer’s ID, we can fetch their orders and see the products they purchased.
Essentially, we are querying relationships in our data.
SQL is your best choice for relational data.
SQL will be the best fit if you need:
Structured data: SQL is best used on structured data with predefined schemas.
Complex Queries: Some complex queries can be for example: “which customers bought the most product in the last month”. SQL can handle these complex relationships and queries easily.
Data Integrity: SQL enforces rules to make sure the data stays accurate. This protects you against accidentally creating illogical records (e.g. Creating an order for a non-existing customer).
So when should you use SQL?
When you need to work with structured, interconnected data where relationships in the data are a dominant characteristic, SQL is an obvious choice (though scalability is always an issue here…).
When to Choose NoSQL
NoSQL thrives off of flexibility. Where SQL provides little flexibility and enforces constraints, NoSQL provides full flexibility for your data.
Imagine you are building a social media platform. Users are posting photos, text, videos, and links. Some leave comments and join groups.
There may be some relationships, but they are more shallow. The data may be relational but it is loosely connected.
NoSQL is usually a best fit for the following:
You need flexibility: you need to store unstructured data and can’t or don’t yet have a defined schema upfront.
You need to scale. You are expecting or already dealing with massive amounts of data and high user traffic. NoSQL is designed to scale horizontally and therefore can handle scale much better than SQL.
You have very low latency requirements: joins are quite slow and can impact the user experience if your application is latency-sensitive (gaming, IoT apps, etc). NoSQL can provide single-digit ms latency.
So NoSQL is an easy choice when you absolutely need high scalability and flexibility from your database. Real-time apps like gaming and social media platforms can benefit greatly from NoSQL databases.
Quick Comparision: SQL Vs NoSQL
The Takeaway
In simple terms, if your data looks like a family tree, with relations at most nodes, SQL is your best bet.
However, if your data looks more like a pile of photos and needs to scale for large audiences, NoSQL is usually a better fit.
Conclusion
In the end, the choice between SQL and NoSQL comes down to understanding your data and how your application is accessing it.
Choose SQL for purely relational data and NoSQL for flexibility and scalability (and low latency).
Use this guide as a reference to make your database choices align with your application’s access patterns and performance needs.
👋 My name is Uriel Bitton and I’m committed to helping you master Serverless, Cloud Computing, and AWS.
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Thanks for reading and see you in the next one!