Difference between SQL and NoSQL

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Overview

These days most of the things are driven by data or you can say that “Data is the new oil”. So in order to store large amount of data we need databases. There are lot of databases available in market, in this article we will focus on two broader types of databases SQL and NoSQL which are majorly used these days, maybe someday you will require one of them in your application so this article will help you to choose the right database for your use case.

In this article, we will see the difference between these two databases and when to use them, but first let’s see what they are in detail.

Scope

This article will talk about differences between two types of databases: SQL and NoSQL. It will discuss how data is stored and when to use each of them.

It will compare the two types based on their Database structure, Scalability, Language, Properties and Support to help you choose between SQL and NoSQL databases for your next project.

What is SQL?

SQL is pronounced as “S-Q-L” or “See-Quel” and stands for Structured Query Language. We use SQL in a Relational Database Management System also known as RDBMS. RDBMS is a software used to store, manage, query, and fetch data stored in a relational database.

In Relational databases, we store data in the form of tables, rows and columns and some of the tables are connected with each other with some relation. Consider the following image: we have different tables and one table is a representation for one entity. We add a new record as a new row in the respective table. This traditional system of managing data is known as an RDBMS.

Tables representation in RDBMS

There are various examples of SQL databases like MySQL, MariaDB, Oracle, PostgreSQL which are used to manage the databases.

What is NoSQL?

NoSQL stands for “Not Only SQL” or “Non SQL”. It is used in non-relational databases. As name suggests, data is not formed in form tables in NoSQL databases. Non relational databases are different from traditional relational databases. Here we store data in the form document which is a key value pair data structure. Consider the following image where the data is stored in the object.

{
name: "sue",
age : 26
status : "A"
groups : ["news", "sports"]
}

In NoSQL we have collections which are nothing but the grouping of these documents. If we compare the documents and collections with RDBMS then the collections are analogous with the table and documents are analogous with the rows. In above example the object in which data is stored is known as JSON(Javascript object notation).

Consider the following image. We have the Employee_Info database in which we have two collections Employee and Projects and these collections have a number of documents.

Employee Information Database

In the above example, we have stored data using collections, each collection has multiple documents. One document stands for one entry. There is no specific structure for NoSQL databases; they can have a variety of structures.
There are 4 major types of NoSql databases:

  • Document databases
  • Key value databases
  • Graph databases
  • Wide-column stores

Difference between SQL and NoSQL

There are various parameters on which we can compare SQL and NoSQL

Comparison based on the Database Structure:

SQL databases are in the form of tables that contain rows and columns, and they have fixed logical schema design. All the data in SQL is arranged in tabular format, it is well suited for complex queries.

SQL Databse Structure

On the other hand, NoSQL databases contain collections and inside every collection, there is a document that contains the data of a single entry. This data is stored in the form of a key-value pair, unlike SQL where we store data under the fixed schema. There are various types of NoSQL databases like graph databases or wide-column stores which are easy to use and understand.

NoSQL Databse Structure

If we try to compare SQL and NoSQL then tables are equivalent to collections, rows are equivalent to documents.

Comparison based on the Scalability:

Both the databases are scalable but when it comes to high scalability NoSQL shines.

SQL databases support vertical scaling, In vertical scaling, we improve the single server by increasing RAM, SSD or CPU. In vertical scaling, we are restricted to the single system and we can improve it as much as we want till the practical limits.

In NoSQL databases, we can do horizontal scaling because they support distributed computing. In Horizontal scaling, we can add another node/computer for better performance. We can add as many nodes as we want and that is why we prefer NoSQL for high scalability because there is no limit for scaling.

Comparison based on the Language:

In SQL databases we use standard structured query language. It is a well-defined, powerful, and widely used language. It has fixed syntax and we can perform complex queries with it. But as we saw due to the restrictive and fixed structure of SQL databases there is a limit of possibilities. We need to define the structure upfront and all data need to follow the same structure. Little change afterward can disrupt the whole system.

NoSQL databases have dynamic schemas and there is no fixed query language to work with them. They have dynamic schema and we can store the data in them within various formats like key-value pair, graph-based, or document-based format which makes their use easy. They can have various schemas under each document, which means we can add data anytime as we go. The queries in NoSQL are faster because there are no joins between tables like SQL which becomes very expensive with large amounts of data.

Comparison based on the Properties:

In the world of SQL databases, the ACID acronym is used heavily.

ACID stands for:

  • Atomicity - Transaction should be performed at once or doesn’t happen at all
  • Consistency - State of the database should remain consistent before and after the transaction.
  • Isolation - One transaction shouldn’t affect another all transactions should be independent
  • Durability - Successful transactions should be reflected even if there is a system failure

These 4 are very important properties for SQL databases and they should be followed by every SQL database.

As NoSQL databases are used with distributed systems it needs to follow the CAP principle.

CAP stands for:

  • Consistency - Every node in the system should share the same, most recent, and successful transaction record with other nodes in the system.
  • Availability - If due to some case there is a connection problem of a node with other nodes in the system then data needs to get sync when there is a connection.
  • Partition Tolerance - If there is a network fault in connection of two nodes the entire system gets partitioned into multiple systems and keeps working continuously. This is a very important property for distributed systems because one node works with multiple nodes/computers.

Comparison based on the Support & deployment:

You get great support from all the vendors of SQL. There are so many consultants available for the deployment help for SQL. Examples of widely used SQL databases are MySQL, PostgreSQL, Microsoft SQL Server, and Oracle, etc.

For NoSQL, you need to rely on community support. The NoSQL communities are in a growing phase and but there are very few experts who have deep knowledge of the NoSql databases, but no doubt it is Nosql community is increasing day by day. Examples of NoSQL databases are MongoDB, CouchDB, Neo4j, RavenDB etc.

The key difference between SQL and NoSQL in a Nutshell:

SQLNo SQL
It is a relational database.It is a non-relational database.
Data is present in the form of tables, rows, and columns.Data is present in the form of collections and documents.
Fixed schema design & structure.Dynamic schema design and structure.
It is vertically scalable and there is a limit to scale.It is horizontally scalable with no limit to scale.
Possible to perform the complex queries.Not possible to perform complex queries.
It follows the ACID(Atomicity, Consistency, Isolation, Durability) property.It follows the CAP(Consistency, Availability, Partition tolerance) principle.
Good support from vendors as well as consultancy for the deployment.It has a growing community so it is difficult to find experts for deployment.
Eg. MySQL, PostgreSQL, Oracle, Microsoft SQL Server, etc.Eg. MongoDB, CouchDB, Neo4j, RavenDB, etc.

When to use SQL?

  • SQL is easiest to work with Relational Databases.
  • SQL is useful when you want to perform complex queries using join.
  • SQL shines if you want to perform quick data storage and retrieval operations.
  • If your application doesn’t require huge scaling then you can prefer SQL.
  • When there is a need for ACID properties in the transactions then SQL is a must.

Also, check out this article on the advantages of SQL to learn why SQL is preferred over others.

When to use NoSQL?

  • The first obvious reason to use NoSQL is if you are designing a distributed system.
  • NoSQL is a must if you want a hierarchical storage structure instead of a table-like structure.
  • NoSQL gives you the flexibility to create dynamic structures and add features as you go.
  • When there is no need for ACID properties during application then you can consider NoSQL.
  • When you want to do horizontal scaling and want to create a huge system of computers in the future.

Conclusion

  • In this article, we saw about the SQL and NoSQL databases, their differences, advantages, disadvantages, and use cases.

  • Both databases come with an enriching set of features and both of them have their different use cases.

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