The traditional SQL database is an optimal solution for highly structured data that’s often required in accounting and e-commerce. But for unstructured data, NoSQL databases are the way to go. MongoDB’s post on NoSQL vs. SQL databases is an article that goes deeper into that subject. But long story short, the biggest difference is that the former is more flexible.
A no sql database uses JSON documents to store data, while an SQL database deals with tables with fixed rows and columns. There are different types of NoSQL databases. Aside from the document model, there are key-value, wide-column store, and graph. But we’ll stick with JSON documents for now.
How does data in NoSql Databases looks like?
First let’s have a look at how data is stored in this kind of database, his is what a JSON document looks like:
In order to dive deeper into the subject of NoSQL, we need to find a solution that handle things for us. For our case I chose MongoDB. I chose MongoD because it’s the most popular document-based database according to Network World, and many other seasoned developers. It doesn’t require much work for setting things up. It’s because it has programs like (Atlas CLI) that can handle a lot of things for you out of the box. We also can store things like tree data structure that we’ve created inside this kind of database.
How to Query a NoSQL Database
Querying a no sql database can vary depending on your operations. Here is what a document-based database query looks like with CRUD operations.
How to create queries using aggregation operations using NoSql database
How to query time series in a NoSQL database
When to Start using a NoSQL Database?
It’s important to define your goals first before deciding on whether or not to build a NoSQL database. Developers typically choose no sql when they need to store massive amounts of unstructured data (for big data applications). A NoSQL database is also a good choice when you need to perform complex queries or real-time processing. SQL databases are typically slower, making them less ideal for applications that need to run certain processes in real-time. In addition, NoSQL databases are well-suited for applications that require high availability and scalability. Because they’re faster than SQL databases, they’re great for use cases like chat or social networking apps. They can also handle many simultaneous requests without slowing down the entire system.
It’s important to note that NoSQL databases are not the best choice for systems with a high volume of transactions. SQL databases are superior because they can handle more complex transactions. That is, they are already equipped with a lot of functions and feature to be able to handle those kinds of cases. But in no sql databases, we are the one who need to handle all of those, even though there are existing solution that can handle that for us, but they don’t have the ease of use that relational databases have out of the box.
If you need more information on when to select which type of database, there’s an article in Enterprise Networking Planet that can helps us chose the right database.
NoSQL vs Relational Database TL;DR
Build a NoSQL if you need to store unstructured data and easily scale it. On the other hand, choose SQL if you’re looking to support transactions and easy queries.
In this article we want through some of the differences between Relational and NOSQL databases. We also saw which one can be useful in what scenario. Feel free to add any comment on other cases that NoSQL databases can be useful.