Why is NoSQL needed? Why are relational databases insufficient? Examples of usage, advantages, storage structures.

NoSQL databases emerged as a response to the limitations of relational databases (SQL) in modern applications with large data volumes, high load, and the need for flexible schemas.

Why relational databases may be insufficient:

• Rigid data schema: changing table structures requires migrations, which is inconvenient with rapidly changing data.
• Scalability: horizontal scaling (sharding) is more difficult to implement in relational databases.
• Performance: with large data volumes and high loads, relational databases can become bottlenecks.

Advantages of NoSQL:

• Flexible schema (schema-less) — can store data of different structures.
• High scalability — easily scaled horizontally.
• Fast processing of large data volumes.

Main types of NoSQL databases and storage structures:

• Document-based (e.g., MongoDB) — store documents in JSON-like objects.
• Key-value (e.g., Redis) — simple storage of key-value pairs.
• Columnar (e.g., Cassandra) — optimized for storing and processing large data volumes by columns.
• Graph (e.g., Neo4j) — for storing and processing graphs and relationships.

Examples of use:

• Large web applications with dynamic data (social networks, online stores).
• Caching and sessions (Redis).
• Analytics and big data processing.
• Log and event storage.

Thus, NoSQL complements relational databases, enabling solutions where flexibility, scalability, and performance are crucial when working with unstructured or semi-structured data.