Software Development

3 Reasons to Use NoSQL over SQL

The Merits of Using NoSQL

3 Reasons to Use NoSQL over SQL
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Deciding between a NoSQL and SQL database can be a very tough choice.

Both have their pros and cons, but today we will focus on 3 definite advantages of NoSQL over SQL.

DISCLAIMER ⚠️: I have nothing against SQL databases, the goal here is to spark a formal discussion over these great technologies.

So without further ado… Let’s dive right in!

1. Sharding

Sharding is a technique used to distribute data from a database across multiple servers.

Sharding is also commonly known as horizontal scaling.

The alternative is vertical scaling, which is a technique that scales a database by upgrading a single server (e.g. adding more RAM, upgrading the CPU).

NoSQL databases are naturally better at horizontal scaling (Sharding), while SQL databases are better at vertical scaling.

The reason NoSQL is better at sharding is because data is self-contained, meaning there is no dependency between the data and the table it belongs to.


To better understand why sharding is easier with NoSQL, take a look at the following example:

Imagine a blogging platform, like medium, storing a blog post object with comments and likes.

NoSQL vs SQL representation of blog post data
NoSQL vs SQL representation of blog post data

In NoSQL, this object would be stored as is, without the need to join data from other tables residing on different servers.

In an SQL database, however, you must JOIN the post with the comments and likes.

This becomes challenging when the SQL database is broken into shards, since comments and views that reside on different servers are much harder to JOIN.

2. Performance At Scale

If we are talking a couple thousand rows of simple data, then performance should be comparable between NoSQL and SQL databases.

Now lets scale to billions of rows with complex relational data.

In this scenario, NoSQL remains performant, since you can shard rows across multiple servers without issue.

Additionally, NoSQL queries scale very well with the increase in data complexity, in fact the query times remain relatively consistent and fast.

On the other hand, sharding massive SQL database is a nightmare, and while vertical scaling is possible, it is not as cost-effective and scalable compared to sharding.

Even worse, as your SQL schema becomes complex, multiple JOIN queries start to pile up and shatter the performance of your database.

3. Simplicity

The core purpose of NoSQL is to let you store large amounts of unstructured data without adhering to a predefined structure.

As a result, NoSQL databases don't enforce rigid schemas like SQL databases do.

This means you spend less time planning the schema before the project even begins, which leads to quicker development.

And even with all this planning, it is likely your database schema will still need refinement at some point.

Refining an SQL schema by removing or modifying existing fields can also be problematic.

This is because you need to migrate data from your existing table into a new one based on the updated schema, which can be time consuming.

With NoSQL however, you can simply remove/modify columns hassle-free!

Conclusion

We have explored 3 reasons to use a NoSQL database instead of an SQL alternative.

The simplicity and performance benefits of NoSQL make it a promising choice for most applications, especially ones that are projected to scale quickly.

While this doesn't mean SQL databases are bad, it just means you should think rethink how you wish to scale your data, and select the right tool for the job.


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