The document compares SQL and NoSQL databases, highlighting SQL's relational structure, fixed schema, and ACID transactions which ensure data integrity, but can be costly to scale and inflexible. In contrast, NoSQL databases offer non-relational structures, flexible schemas, and horizontal scalability suitable for large volumes of data, but may provide eventual consistency and lack a standard query language. Examples of SQL databases include MySQL and Oracle, while NoSQL examples include MongoDB and Cassandra.

1. SQL vs NoSQL
Gabriel Garcia

2. SQL (Structured Query
Language) Databases

3. Characteristics

4. Structure
• SQL databases are relational,
meaning data is organized into
tables with rows and columns. Each
row represents a unique record,
and each column represents an
attribute of that record

5. Query Language
• They use SQL as the standard
language for querying and
manipulating data. SQL is a
declarative language, meaning it
describes what data to retrieve, not
how to retrieve it.

6. Fixed Schema
• SQL databases have a rigid,
predefined schema. You need to
define the table structure (schema)
before inserting data, specifying
the data types for each column.

7. Transactions
• They support ACID (Atomicity,
Consistency, Isolation, Durability)
transactions, ensuring data
integrity and reliability.

8. Advantages

9. Consistency
• The rigid schema ensures data
consistency and maintains
referential integrity.

10. Support and
Maturity
• SQL databases have been around
for a long time, providing broad
support and extensive
documentation.

11. Disadvantages

12. Vertical Scalability
• Typically, SQL databases scale
vertically (by improving hardware),
which can be costly.

13. Limited Flexibility
• Changing the schema of an SQL
database can be challenging and
time-consuming.

14. Examples of SQL Databases
MySQL PostgreSQL Microsoft SQL
Server
Oracle
Database

15. NoSQL (Not Only SQL)
Databases

16. Characteristics

17. Structure
• NoSQL databases are non-
relational and can store data in
various formats, such as
documents (JSON), graphs, key-
value pairs, and columns. They do
not require a fixed schema,
allowing for more flexible data
storage.

18. Flexibility
• They can handle unstructured or
semi-structured data, allowing
diverse information to be stored
without a predefined structure.

19. Horizontal
Scalability
• NoSQL databases typically scale
horizontally, meaning you can add
more servers to handle more data
and traffic, which is ideal for large
volumes of data and cloud-based
applications.

20. Advantages

21. Scalability
• They can handle large volumes of
data and are easily scalable
horizontally.

22. Flexibility
• They adapt better to changing data
requirements since they do not
require a fixed schema.

23. Disadvantage
s

24. Eventual
Consistency
• Instead of providing immediate
consistency, many NoSQL
databases offer "eventual
consistency," which might be less
suitable for applications requiring
real-time precision.

25. Lack of Standard
• There is no standard query
language like SQL for NoSQL
databases, which can make
transitioning between different
systems more complex.

26. Examples of NoSQL Databases
MongoDB
(document-
based)
Cassandra
(column-based)
Redis (key-value) Neo4j (graph-
based)