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Non-relational databases that are made for high performance, scalability, and flexible data models with unstructured or semi-structured data are referred to as NoSQL (Not Only SQL). NoSQL systems, in contrast to conventional SQL databases, are excellent at managing distributed systems, huge data, and real-time applications. They also don’t require defined schemas.

Types of NoSQL Databases

Document stores, such as CouchDB and MongoDB

• Keep data in documents that resemble JSON.
• Perfect for catalogs and content management.

Key-Value Stores (like DynamoDB and Redis)

• Basic “key-value” pairs for quick searches.
• used for session management and caching.

Column-Family Stores (like HBase and Cassandra)

• designed with distributed, large-scale data in mind.
• IoT is common in time-series data.

Graph databases, such as ArangoDB and Neo4j

• Store node and edge relationships.
• Ideal for fraud detection and social networks.

Advantages of NoSQL

* Scalability: Horizontal scaling (distributed clusters).
* Flexibility: Schema-less, dynamic data structures.
* High Performance: Optimized for read/write-heavy workloads.
* Fault Tolerance: Built-in replication & sharding.

When to Use NoSQL?

* Handling unstructured/semi-structured data (JSON, XML).
* Big Data & real-time apps (e.g., social media, gaming).
* Microservices & cloud-native apps (scales easily).
* High-speed transactions (e.g., e-commerce carts).

Popular NoSQL Databases

• MongoDB (Document)
• Redis (Key-Value)
• Cassandra (Column-family)
• Neo4j (Graph)
• Amazon DynamoDB (Managed Key-Value/NoSQL)

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