Sr No
|
SQL
|
NOSQL
|
1
|
SQL
databases provide store of related data tables
|
NOSQL
databases store JSON-like filed value pair documents
|
2
|
SQL tables create a
strict data template, so it’s difficult to make mistakes
|
NoSQL is more flexible.
It can store any data anywhere which leads to consistency issues.
|
3
|
SQL
has schema information such as primary keys, indexes and relationships.
|
In
NoSQL data can be added anywhere anytime. There is no need to specify
document design. NOSQL generally adds id value automatically to each
document.
|
4
|
When data requirement is
clear SQL is more suitable
|
When data requirement is
not clear NOSQL is more suitable
|
5
|
SQL
enforces data integrity rules using foreign key constraints
|
Ideally
one documents has all the information.
|
6
|
SQL transactions ensure
that either all operations are successful or failed.
|
Updating document is
atomic. But there are no transaction equivalent of updating multiple documents
|
7
|
SQL
is lightweight declarative language
For
example :
INSERT INTO book (
`ISBN`, `title`, `author`
)
VALUES (
'9780992461256',
'Full
Stack JavaScript',
'Colin
Ihrig & Adam Bretz'
);
UPDATE book
SET price = 19.99
WHERE ISBN = '9780992461256'
|
NOSQL
queries are JSON-like.
For
example :
db.book.insert({
ISBN: "9780992461256",
title: "Full Stack
JavaScript",
author: "Colin Ihrig &
Adam Bretz"
});
db.book.update(
{ ISBN: '9780992461256' },
{ $set: { price: 19.99 } }
);
|
9
|
A well-designed SQL database will almost certainly perform
better than a badly designed NoSQL equivalent and vice versa.
|
Generally NOSQL is
faster than SQL
|
10
|
To
distribute load on multiple servers is tricky in SQL
|
Very
easy to scale
|
11
|
SQL faces less issues as
compared to NOSQL
|
System admins has less
experience to NOSQL databases which lead to security or system problems.
|
12
|
Where
to use SQL:
1. Data requirement is known
2. Data integrity is essential
|
Where
to use NOSQL:
2. Speed and scalability is imperative
|
SQL vs NOSQL
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