Difference Between SQL and NoSQL

When choosing a database, the biggest decision is whether to choose a relational (SQL) or non-relational (NoSQL) data structure. While both databases are viable options, there are certain key differences between the two databases that users must keep in mind when making their decision.

Main differences:

1. Type

SQL database is mainly called Relational Database (RDBMS); while NoSQL databases are mainly known as non-relational databases or distributed databases.

2. Language

SQL database definition and operation is based on data-based Structured Query Language (SQL). This language is very powerful when viewed from the side. SQL is one of the most versatile and widely used options, making it a safe choice, especially for complex queries. But on the other hand, it can be restrictive. SQL requires you to use a predefined schema to determine the structure of your data before use. Additionally, all your data must follow the same structure. This can require a lot of upfront preparation, meaning changes in structure are both difficult and disruptive to the entire system.

NoSQL databases have dynamic schemas for unstructured data. Data is stored in multiple ways, meaning it can be document-oriented, column-oriented, graph-based or organized as KeyValue storage. This flexibility means that documents can be created without first defining the structure. Each document can also have its own unique structure. The syntax varies from database to database, and you can add fields at any time.

3. Scalability

In almost all cases, SQL databases are vertically scalable. This means you can increase the load on a single server by adding features like RAM, CPU, or SSD. But on the other hand, NoSQL databases can scale horizontally. This means you can handle more traffic through sharding or adding more servers to your NoSQL database. It's similar to adding more floors to the same building rather than adding more buildings nearby. So NoSQL can eventually become larger and more powerful, making these databases the first choice for large or changing data sets.

4. Structure

SQL databases are table-based, on the other hand NoSQL databases are key-value pairs, document-based, graph databases or wide column stores. This makes relational SQL databases a better choice for applications that require multi-row transactions (such as accounting systems) or legacy systems built for relational structures.

5. Properties followed

SQL databases follow ACID properties (atomicity, consistency, isolation and durability), while NoSQL databases follow Brewers CAP theorem ( consistency, availability and partition tolerance).

6. Support

All SQL databases from its vendors are well supported. Additionally, there are many independent consultancies that can help you with large-scale deployments using SQL databases, but for some NoSQL databases you still need to rely on community support, and there are limited external experts available to set up and deploy large-scale NoSQL deployments.

Some examples of SQL databases include PostgreSQL, MySQL, Oracle, and Microsoft SQL Server. NoSQL database examples include Redis, RavenDB Cassandra, MongoDB, BigTable, HBase, Neo4j, and CouchDB.

Key differences between SQL vs NoSQL:

SQL	NOSQL
Relational Database Management System (RDBMS)	Non-relational or distributed database system.
These databases have fixed or static or predefined schemas	They have dynamic schemas
These databases are not suitable for Tiered data storage.	These databases are best suited for hierarchical data storage.
These databases are best suited for complex queries	These databases are less suitable for complex queries
Verticlly scalable	Horizontally scalable

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