What is the difference between SQL and NoSQL databases?

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The main difference between SQL and NoSQL databases lies in how they store, manage, and query data.

SQL Databases (Relational):

  • Structured Data: Store data in predefined tables with rows and columns (schema-based).

  • Query Language: Use Structured Query Language (SQL) for querying and managing data.

  • ACID Compliance: Strong support for Atomicity, Consistency, Isolation, Durability, ensuring reliable transactions.

  • Examples: MySQL, PostgreSQL, Oracle, Microsoft SQL Server.

  • Best For: Applications requiring complex queries, transactions, and relational data (e.g., financial systems, ERPs).

NoSQL Databases (Non-relational):

  • Flexible Schema: Store unstructured or semi-structured data. Data can be stored as key-value pairs, documents, graphs, or wide-columns.

  • Scalability: Designed for horizontal scaling, making them suitable for handling large volumes of data across distributed systems.

  • Eventual Consistency: Often prioritize availability and partition tolerance over strict consistency (CAP theorem).

  • Examples: MongoDB (document), Redis (key-value), Cassandra (wide-column), Neo4j (graph).

  • Best For: Big data, real-time web apps, content management, IoT, and applications with rapidly changing data.

Summary:

  • SQL = Structured, schema-based, relational, strong consistency.

  • NoSQL = Flexible, schema-less, non-relational, scalable.

Choosing between them depends on your application's data structure, scalability needs, and consistency requirements.

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