What is the difference between SQL and NoSQL?

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SQL vs NoSQL: Key Differences

1. Data Model

  • SQL (Relational Databases):
    Data is stored in structured tables with rows and columns. Each table has a fixed schema defining the data types and relationships (e.g., MySQL, PostgreSQL, SQLite).

  • NoSQL (Non-relational Databases):
    Data is stored in flexible formats such as documents, key-value pairs, wide-column stores, or graphs. Schemas can be dynamic or absent (e.g., MongoDB, Cassandra, Redis).

2. Schema

  • SQL: Requires a predefined schema. Changes to structure (adding columns) need migrations and can be complex.

  • NoSQL: Schema-less or flexible schema. Data models can evolve easily without downtime.

3. Scalability

  • SQL: Typically scales vertically (upgrading hardware), though some support horizontal scaling with difficulty.

  • NoSQL: Designed for horizontal scaling (distributing data across multiple servers) which suits big data and real-time web apps.

4. Transactions & Consistency

  • SQL: Supports ACID (Atomicity, Consistency, Isolation, Durability) transactions ensuring reliable, consistent data.

  • NoSQL: Often provides eventual consistency and BASE (Basically Available, Soft state, Eventual consistency) model, prioritizing availability and partition tolerance over strict consistency.

5. Use Cases

  • SQL: Ideal for complex queries, multi-row transactions, structured data, and applications needing strong consistency (e.g., banking systems).

  • NoSQL: Best for large volumes of unstructured or semi-structured data, rapid development, and apps requiring flexible schemas (e.g., social media, IoT, real-time analytics).

6. Query Language

  • SQL: Uses structured query language (SQL) which is powerful and standardized.

  • NoSQL: Uses varied query methods depending on database type; for example, JSON-based queries in MongoDB.

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