Summary  
NoSQL databases are non-relational data management systems that support flexible, schema-less storage of semi-structured or unstructured data and enable horizontal scalability for distributed data storage and retrieval.

General domain of usage  
Large-scale data storage and retrieval

**NoSQL**, which stands for **"Not Only SQL"**, refers to a broad category of database management systems that are designed to handle a wide variety of data models, particularly **non-relational** or **semi-structured data**.    
 Unlike traditional relational databases, which use structured query language (SQL) to define and manipulate data, NoSQL databases offer a more flexible schema design and are optimized for large-scale data storage and retrieval.

### Why NoSQL?

NoSQL databases are designed to handle:

- **Unstructured or Semi-structured Data**: data that does not fit neatly into tables, rows, and columns, such as JSON documents, key-value pairs, graphs, and wide-column stores;
- **High Scalability**: horizontal scaling, where databases can distribute data across **many servers**, making it easier to handle large volumes of data and high transaction loads;
- **Flexibility**: dynamic schemas that allow for the addition of new fields without the need for database downtime or complex schema migrations.


A real-life case where NoSQL is preferable is in social media platforms, such as Facebook or Twitter.
These platforms handle massive amounts of unstructured data, including user posts, comments, likes, and multimedia content, which are continuously generated at high velocity. NoSQL databases provide the scalability and flexibility needed to efficiently manage and quickly retrieve this diverse and dynamic data without the constraints of a fixed schema.

Note

Stores data in JSON-like documents, providing flexibility and scalability for handling unstructured data.

Highly scalable and distributed database designed to handle large amounts of data across many commodity servers with no single point of failure.

In-memory data structure store, used as a database, cache, and message broker, known for its high performance.

Optimized for storing and querying highly interconnected data, making it ideal for applications like social networks and recommendation engines.

Uses JSON for documents, JavaScript for MapReduce queries, and HTTP for its API, focusing on ease of use and scalability.

Which of the following is NOT a type of NoSQL database?

Begin an exciting journey through SQL with Advanced Techniques in SQL. Learn about the important ACID properties that help keep data accurate in database transactions. Discover advanced ways to optimize your queries to improve database performance. Explore special SQL features like window functions, triggers, Data Control Language (DCL), and NoSQL databases. This will help you handle modern database management confidently and effectively.

Now we explore the basic principles of ACID (Atomicity, Consistency, Isolation, Durability) in database management. Learn how these principles ensure reliable transactions by guaranteeing complete operations, keeping data consistent, isolating concurrent transactions, and ensuring permanent data storage.

Explore how to enhance the efficiency of your SQL queries through index optimization. Delve into the significance of indexes in database performance, learning how to design, implement, and utilize them effectively. Discover strategies for choosing the appropriate indexes, understanding their impact on query execution plans, and optimizing query performance through index selection and utilization.

This section explores pivotal topics such as Triggers, Window Functions, and DCL (Data Control Language), offering comprehensive insights into their implementation and optimization strategies. Furthermore, it navigates the landscape of NoSQL DBMS, providing a thorough understanding of its architecture, advantages, and practical applications.

NoSQL

Why NoSQL?

NoSQL database types