The document compares SQL and NoSQL databases, outlining their definitions, structures, and ideal use cases. SQL is a traditional, structured database suited for consistent data, while NoSQL is flexible and caters to large volumes of unstructured or semi-structured data. It highlights key differences in schema, scalability, transaction management, and performance of both database types.

2. SQL VS NoSQL:
Top 10 Head-to-
Head
Comparisons
Are you confused while choosing the modern
database? Or don't know whether SQL or
NoSQL; which one to choose? SQL refers to a
decades-old database but is still ubiquitous
and effectively being used by Analysts,
Engineers, data scientists, and IT decision-
makers. However, the increasing volumes of
unstructured data, process chunks of data,
and the need for storage availability spark
interest in different technologies such as
NoSQL.

3. What is
Structured
Query language
(SQL)?

4. SQL is a programming language that differs from a general-purpose
programming language such as Python, Java, and JavaScript. It has a specific
purpose: to access and manage data in relational databases. It uses relations
(referred to as tables) with a schema to manage and store data.
Some of the relational database examples which use SQL are:
• Oracle
• Microsoft SQL server
• Ingres
• Microsoft office
Access
• IBM DB2
• Sybase
• Google Cloud SQL
• Amazon RDS
• PostgreSQL

5. What is Non- SQL or
Not only SQL
(NoSQL)?
It is a non-tabular and non-
relational database with specific
data models such as document,
key-value, and graph formats to
create modern applications. It is
used for distributed data that
requires a large stack of storage
needs and can effectively store
structured, unstructured, semi-
structured, and polymorphic data.

6. Some of the
common
NoSQL
database
examples are:
 MongoDB
 Couchbase
 Amazon's Dynamo DB
 CloudDB
 Apache's CouchDB
 MarkLogic
 Oracle NoSQL
 HBase
 Apache's Cassandra DB
 Redis

7. Comparison SQL NoSQL
Key Purpose
It can be used for data
1.Storage
2.Deletion
3.Updation
4.Insertion
5.Retrieval of data
It can be used for the
maintenance and retrieval of
different types of data
1.Structured
2.Unstructured
3.Semi-structured
4.Polymorphic
Schema
Rigid Schema (structured
data)
Flexible Schema
(unstructured data)
Data Structure
SQL Data structures
Table-based
1.NoSQL Data
structures Document-based
2.Key-value
3.Graph-based
4.Wide Column
Scalability
Vertically scaled( add big
servers)
Horizontally scaled(add more
servers)

8. Ideal use cases
1.It is well-suited
for Complex queries
2.Multi-row transactions
3.Dynamic queries
4.Legacy systems that built
around the relational
structure
1.It is well suited
for Unstructured data or
document
2.Real-time data
3.Cloud computing
4.Agile business
5.Non-complex queries
Scalable queries due to
changing environments
Hardware
Require powerful hardware to
foster vertical scaling
Requires commodity hardware
to foster horizontal scaling
Database transactions
Follow ACID (atomicity,
consistency, isolation, and
durability) properties
Follow BASE (basic availability,
soft-state, and eventual
consistency)

9. Architectural Relational Non-relational
Key Features
1.Features of SQL Cross-
platform support
2.Multi-level Security
3.Free
1.Features of NoSQL High
performance
2.Scalability
3.Flexibility
Normalization & Joins
Normalization & joins are
required
Denormalization & joins are
not required

10. SQL database is the preferred option if
you are handling structured data that
doesn't change much over time.
You can consider a NoSQL database if you
handle a large chunk of data with little
structure. If you are searching for the best
software development company in
USA that provides an efficient and
streamlined database management
solution for your enterprise
Final Thought:
SQL vs NoSQL

11. Contact US
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