Saturday, March 26, 2022

MySQL vs NoSQL (non relational DB) - Pros and Cons

Hello guys, if you are wondering whether to choose a NoSQL database like MongoDB, Cassandara, or MySQL for your application then you have come to the right place. In an earlier article, MySQL vs PostgreSQL I had shared the pros and cons of choosing MySQL over PostgreSQL for your application, and in this article, I am going to show the benefits and drawbacks of choosing MySQL over NoSQL or vice-versa. 

What is NoSQL?

A non-relational database is one that does not employ the relational database's tabular schema of rows and columns. Its storage strategy, on the other hand, is tailored to the sort of data it stores. Databases that aren't relational are referred to as NoSQL databases, which stands for "Not Only SQL." Non-relational databases, unlike relational databases, may employ a variety of query languages.

NoSQL databases are divided into four categories.
  • Document-oriented databases, also known as document stores, are databases that are used to store, retrieve, and manage document-oriented data. Each key in a document database is frequently paired with a sophisticated data structure (called a document).

  • Key-Value Stores — A key-value store is a database that employs several keys, each of which is linked to just one value in a collection. Consider it a dictionary. Among the NoSQL database types, this is one of the most basic.

  • Wide-Column Stores — unlike a relational database, this database employs tables, rows, and columns, but the names and formats of the columns can change from row to row in the same table.

  • Graph Stores - A graph database represents and stores data using graph structures for semantic searches, such as nodes, edges, and attributes.
As more firms turn to big data for research and reporting, non-relational databases are becoming increasingly popular. NoSQL databases provide additional flexibility because vital data may not necessarily fit into a pre-defined structure.

MySQMySQL vs NoSQL (non relational DB) - Pros and Cons

When to use SQL vs NoSQL?

Are you considering switching from SQL to NoSQL but aren't sure if it's the appropriate move?

The distinction between SQL and NoSQL databases boils down to the distinction between relational and non-relational databases. When to use SQL and when to utilize NoSQL relies on the type of data you're keeping and the best manner to store it. Both categories store data, although they do it in distinct ways.

The true answer for SQL vs NoSQL is that it depends on what you're building, the limits imposed by who you're developing for, and the desired outcome.

While NoSQL is gaining popularity and adoption, it is not a replacement for SQL. It's only a different alternative. Although it is sometimes necessary to choose one over the other, many development teams choose to employ both.

Now, let's compare each of them to the factors that matter.

SQL vs NoSQL in terms of scalability

One of the most serious problems with SQL is its lack of scalability. SQL was created with scalability in mind. The term "scaling up" or "scaling vertically" refers to the addition of additional hardware, RAM, computing power, and other resources in order to enhance capacity. 

With SQL we’re constrained since we will certainly max out on capacity and scaling up is costly. Scaling out SQL is conceivable, but it takes a lot of time and money (partitioning, sharding, clustering, and so on).

When it comes to scalability, the main distinction between SQL and NoSQL is this: NoSQL databases are built to scale out and make use of cloud computing. We are adding resources to a single node whether expanding out or horizontally (a computer or server). A single database can be used by several nodes. We can easily add (or delete) nodes when we scale out (or back in). 

This makes NoSQL a fantastic match for the cloud. Because it can scale out, you will be leveraging the scalability benefits of the cloud. You can run SQL on Azure, for example, but you will be constrained in your capacity to scale.

performance of MySQL vs NoSQL

SQL vs NoSQL in terms of speed

NoSQL is easier to design because of its capacity to store large volumes of data in a flexible manner. A database can be created without a formal database model. Without identifying the type of data in advance, store a wide range of data. 

Without having to rewrite the schema, you may add new data types. Fast-paced, agile development teams work well with NoSQL. As the scope and needs change, it enables quick adjustments to the database structure.

This isn't to say that SQL is sluggish. There's probably no need to adopt NoSQL if your data is highly organized and you expect minimal modification. Your engineers won't stumble into difficulties they can't address since SQL is mature and backed by a large technical community. 

You're more likely to come across difficult difficulties using NoSQL that don't have published answers, which might cause delays. 

Standardization is also lacking in NoSQL databases. MongoDB and Cassandra DB, for example, are both ideal NoSQL databases to learn for an engineer new to NoSQL. However, because NoSQL lacks standards, an engineer who first learns MongoDB may struggle with Cassandra DB.

SQL is also recognized for its powerful capabilities and tools. Tools for monitoring, backing up, and maintaining NoSQL databases are provided by NoSQL frameworks. SQL is still more powerful nowadays. However, as NoSQL develops, more functionalities become accessible. Some instances are as follows:

While both SQL and NoSQL databases offer high availability and auto-replication (automatically interacting with another instance when one fails), SQL needs configuration, whereas many NoSQL databases come with these capabilities pre-installed.

You'll require sharding and partitioning if you're dealing with a multi-tenant application (separating very large databases into smaller, faster, more easily managed parts). Additional code is required to do this with SQL databases. These functionalities are built-in to NoSQL databases (such as CosmosDB).


That's all about MySQL vs NoSQL. There's a lot to think about and navigate. We started by looking at the questions we ask. We then get into greater detail about which type of NoSQL database to use, which NoSQL framework is the best and why, how and when to migrate old SQL to NoSQL, how to perform a cost comparison, how to help developers, and how to avoid common problems.

My Other SQL Articles and Tutorials you may like
Thanks for reading this article so far. If you like this MySQL vs NoSQL comparison and my analysis of the pros and cons of choosing MySQL vs Non-Relationional DB then please share it with your friends and colleagues. If you have any questions or feedback then please drop a note. 

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