📚 NoSQL Databases and Similar Technologies

1. What is NoSQL?

• NoSQL stands for "Not Only SQL" or "Non-relational".
• It refers to a broad class of database systems that do not use the traditional relational model.
• Designed to handle large volumes of unstructured or semi-structured data, with flexible schemas, high scalability, and high performance.

2. Why NoSQL?

• RDBMS struggles with scaling horizontally for big data and distributed environments.

• NoSQL databases handle:

  • Huge data volumes (big data).
  • High velocity data (real-time apps).
  • Diverse data formats (JSON, XML, graphs).

• Support for schema flexibility and distributed architectures.

3. Types of NoSQL Databases

4. Key Characteristics of NoSQL

5. CAP Theorem Recap

• No distributed system can simultaneously guarantee:

  • Consistency (C)
  • Availability (A)
  • Partition Tolerance (P)

• NoSQL databases often choose between:

  • CA (Consistency + Availability)
  • AP (Availability + Partition tolerance)
  • CP (Consistency + Partition tolerance)

6. Examples of NoSQL Technologies

7. When to Use NoSQL?

• Data is semi-structured or unstructured.
• You need high throughput and low latency.
• Applications require horizontal scalability.
• Schema may evolve rapidly.
• Complex relationships or graph data is important.

8. Advantages

• Flexible data model adapts to changing needs.
• Can handle big data and real-time workloads efficiently.
• Simplifies scaling and distributed data management.
• Usually simpler to develop with for non-relational data.

9. Limitations

• Often lack ACID transactions (though improving).
• Query languages can be less powerful than SQL.
• Some tools and skills are less mature.
• Data consistency can be eventual, not immediate.

10. Summary Table