What is the difference between SQL and NoSQL databases?
The database is the systematic collection of data. They support the storage and manipulation of data. With the help of databases, you can manage your data easily.
While starting with databases, it’s common to get confused between SQL and NoSQL databases. In this article, we’re going to learn all the differences between these two and where to use them.
What is SQL?
SQL stands for ‘Structured Query Language’. These are classified as RDBMS (Relational database management system). A relational database is a collection of information that organizes data in predefined relationships where data is stored in relations or tables of rows and columns. RDBMS is software used to manage, store, query, and retrieve data stored in a relational database. SQL is free and open-source as well as a commercial which means it has community support. When your primary focus is on data consistency and data integrity, SQL is a much better option. To retrieve data, you need to execute queries that are dynamic and complex. It deals with schemas that are fixed or predefined.
What is NoSQL?
NoSQL stands for ‘Not-only SQL’. These are user-friendly, easier to use and provide higher performance. NoSQL is known as DDMS (Distributed database management system). A distributed database is a collection of multiple, logically interrelated databases distributed over a computer network. When you are dealing with a huge volume of unstructured data, NoSQL is a much better option. However, it is not good for complex queries. It deals with the dynamic schema as data is not structured.
Difference between SQL and NoSQL
|Classified as RDBMS (Relational database management system)||Known as DDMS (Distributed database management system)|
|Preferred for complex queries||Preferred for hierarchical large data storage|
|Best suited for multi-row transaction applications as they are table-based databases||Best suited when there are a lot of changes in the data|
|Deals with a fixed, pre-defined schema||Don’t have a pre-defined schema|
|It is vertically scalable. Vertical scaling refers to increasing the processing power of a single server or cluster||It is horizontally scalable which means data is referred to as splitting row-wise into multiple tables which reduces the time taken to fetch data|
|For example: Postgres & MySQL||For example: MongoDB, BigTable, Redis, etc|
When to use SQL vs NoSQL?
- When working with related data
- Best suited for multi-row transaction applications
- When your primary focus is data integrity
- When you want to execute complex queries
- When you want to avoid data redundancy and data duplication
Big tech companies including Uber, Netflix, Google, Facebook, and Amazon, which build their database systems, use SQL to query and analyze data.
- Better suited for big data
- When flexibility is an important requirement
- When dealing with unstructured data
- When there is a need for fast availability of big data
- When the dataset is extensive
Amazon, Google, and Netflix use NoSQL systems because they are dependent on large volumes of data not suited to a relational database.
Depending on your circumstances, you can use either of the databases as they have their advantages and disadvantages. While a relational database is a vital and most popular option but it is not suitable for big data analysis. You can choose SQL or NoSQL solely depending on the database of your project.
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