SQL vs No SQL

SQL vs No SQL

Find out the differences between SQl vs Nosql Databases. And their various use cases:-

 

From Software developers to Data Analysts to Data Scientists everybody is familiar with Databases and SQL (Structured Query Language). SQL has been with us from the past 50+ years and was developed by IBM researchers and still today it is as relevant to us as it has always been. Every developer must have a good understanding of Databases and Differences between SQL vs Nosql.

 

SQL is a programming language used to interface with relational databases. (Relational databases are basically records of data stored in the form of tables with links between them.) and Nosql is a class of Non-Relational databases which doesn’t use SQL as a query language to make changes in the stored data.

 

Let’s find out what each database type is and their advantages and disadvantages with various of their applications.

 

What is a SQL Database?

 

SQL, which stands for “Structured Query Language,” is the programming language that’s been widely used in managing data in relational database management systems (RDBMS).

 

In Relational Databases, data is stored in rows and tables that are linked in various ways. One table record may link to one other or to many others, or many table records may be related to many records in another table. These relational databases, which offer fast data storage and recovery, can handle great amounts of data and complex SQL queries.

 

What is a Nosql database?

 

 

Nosql is a Non Relational Database, meaning it allows various different structures than a table format of SQL Database like JSON Documents; Key:value pairs, wide-column; Graphs: nodes and edges, etc.

 

 

The key differences between Sql and Nosql Databases:

1.  Language: 

SQL databases are primarily called Relational Databases which add and manipulate data through sql (structured query language) queries. It is one of the most widely used query languages for databases; it originated in the 1970s which also makes it the oldest. SQL requires you to use predefined schemas to determine the structure of the data before you start working with it. Whereas NoSQL has dynamic schemas for unstructured data. Data is stored in many different ways, the data stored in NoSQL databases can be column-oriented, document-oriented, graph based, or key:value pairs. This dynamic flexibility means that documents can be created without having to define the structure of the database first. 

 

2.          Structure:

SQL database schema organizes data using tables with columns or attributes and rows of records. Because SQL works with such a predefined schema, it requires organizing and structuring data before starting with the SQL database. On the other hand, the structure in the NoSQL database varies, the databases are either key-value-pairs, document based, graph databases with nodes and edges etc., so the structure is very different from that of SQL Databases.

 

3.          Scalability:

SQL databases are mostly vertically scalable, which means you can increase the load on a server by migrating to a larger server that adds more CPU, RAM or SSD capability. While vertical scalability is used most frequently in SQL databases, SQL databases can also scale horizontally through sharing, although that’s not well-supported. The NoSQL database can become very powerful by adding more servers, which makes NoSQL databases the preferred databases for a very large number of datasets.

 

4.          Support:

Because SQL databases have a long history now, they have huge communities, vendors, independent consultants, etc. but for NoSQL databases there is not that much support. There is community support and only limited experts for deploying your large scale NoSQL deployments.

 

Get Started with SQL:

 

So, now you know the basic differences between the two, and why these databases are important and which one may suit you better for your backend environment. 

 

If you want to learn more about SQL and master the language to handle and manage your database, visit our course by an industry expert, who is a Data Analyst and currently working in PWC.