NoSQL Databases

Overview

NoSQL (Not Only SQL) databases are non-relational databases designed for specific data models, horizontal scalability, and high availability. They emerged in the late 2000s to address limitations of traditional RDBMS for web-scale applications: massive data volumes, high write throughput, flexible schemas, and distributed architectures.

Detailed Explanation

Why NoSQL?

flowchart TD
    A[Why NoSQL?] --> B[Scale Beyond<br/>Single Machine]
    A --> C[Flexible Schema]
    A --> D[Specific Data Models]
    A --> E[High Availability]

    B --> B1[Horizontal scaling]
    B --> B2[Distributed by design]
    C --> C1[No fixed schema]
    C --> C2[Handle heterogeneous data]
    D --> D1[Key-value, document, graph, column]
    E --> E1[Eventually consistent]

    style A fill:#e1f5fe

NoSQL vs. RDBMS

ACID vs. BASE

flowchart LR
    A[ACID<br/>RDBMS] --> B[Atomicity<br/>Consistency<br/>Isolation<br/>Durability]
    C[BASE<br/>NoSQL] --> D[Basically Available<br/>Soft state<br/>Eventually consistent]

    style A fill:#ffcdd2
    style C fill:#c8e6c9

Types of NoSQL Databases

flowchart TD
    A[NoSQL Types] --> B[Key-Value<br/>Redis, DynamoDB]
    A --> C[Document<br/>MongoDB, CouchDB]
    A --> D[Column-Family<br/>Cassandra, HBase]
    A --> E[Graph<br/>Neo4j, Amazon Neptune]

    B --> B1[Simple, fast, cache-friendly]
    C --> C1[Flexible, nested data]
    D --> D1[Wide rows, time-series]
    E --> E1[Relationships, traversals]

    style B fill:#e1f5fe
    style C fill:#c8e6c9
    style D fill:#fff3e0
    style E fill:#f3e5f5

Comparison at a Glance

CAP Classification

When to Use NoSQL vs. RDBMS

flowchart TD
    A{Choose Database} --> B{Complex queries<br/>with JOINs?}
    B -->|Yes| C[RDBMS]
    B -->|No| D{Schema flexible<br/>or evolving?}
    D -->|Yes| E{Data model?}
    D -->|No| C
    E -->|Simple key-value| F[Key-Value Store]
    E -->|Nested/hierarchical| G[Document Store]
    E -->|Time-series/wide rows| H[Column-Family]
    E -->|Relationship-heavy| I[Graph Database]

    style C fill:#ffcdd2
    style F fill:#c8e6c9
    style G fill:#c8e6c9
    style H fill:#c8e6c9
    style I fill:#c8e6c9

Topics in This Section

1. Key-Value Stores

Redis, DynamoDB, Riak — simple, fast, horizontally scalable.

2. Document Databases

MongoDB, CouchDB — flexible schema, nested data, rich queries.

3. Column-Family Stores

Cassandra, HBase — wide rows, time-series, high write throughput.

4. Graph Databases

Neo4j, Amazon Neptune — relationships, traversals, social networks.

5. NewSQL

CockroachDB, TiDB, Spanner — SQL + distributed scalability.

Interview Focus Areas

1. When to choose NoSQL over RDBMS? — Schema flexibility, scale requirements, data model fit
2. What are the trade-offs? — Consistency vs. availability, joins vs. scalability
3. How does each type work? — Data model, query patterns, scaling mechanism
4. What is BASE? — Basically Available, Soft state, Eventually consistent
5. Polyglot persistence — Using multiple database types for different needs

Cross-References

• CAP Theorem — NoSQL trade-offs
• Consistency Models — NoSQL consistency guarantees
• Sharding — how NoSQL scales
• Replication — how NoSQL replicates
• Buffer Management — underlying storage

Cross References

• Key-Value
• Document
• Column Family
• Graph
• Relational Model