Module 1 - Data Storage

SQL vs NoSQL Deep Dive

Understanding when to use relational databases versus NoSQL alternatives.

1The Core Difference

Simple Analogy

SQL (Spreadsheet): Like Excel with strict columns. Every row must follow the same structure. You can link sheets together (JOIN). Great for structured, related data.

NoSQL (Filing Cabinet): Each folder can contain different documents. No fixed structure. Fast to find a specific folder, but harder to search across all folders.

SQL (Relational): Structured tables with predefined schemas, relationships via foreign keys, ACID transactions, powerful query language.

NoSQL: Flexible schemas, optimized for specific access patterns, horizontal scalability, eventual consistency (usually).

2SQL Database Strengths

ACID Transactions

Atomicity, Consistency, Isolation, Durability. Critical for financial data.

Complex Queries

JOINs across tables, aggregations, subqueries. SQL is incredibly expressive.

Strong Consistency

Read-after-write consistency by default. No stale data concerns.

Mature Ecosystem

Decades of tooling and expertise. PostgreSQL, MySQL are battle-tested.

Choose SQL when: Data has clear relationships, need complex queries, ACID required, schema is stable.

3NoSQL Database Types

Document Store

MongoDB, CouchDB

JSON-like documents with flexible schema. Good for content, profiles.

Key-Value Store

Redis, DynamoDB

Simple key-value pairs. Fastest for lookups. Good for caching, sessions.

Wide-Column Store

Cassandra, HBase

Rows with dynamic columns. Good for time-series, IoT data.

Graph Database

Neo4j, Neptune

Nodes and edges. Perfect for social networks, recommendations.

4Comparison Table

Aspect	SQL	NoSQL
Schema	Fixed, predefined	Flexible, dynamic
Scaling	Vertical (mostly)	Horizontal
Consistency	Strong (ACID)	Eventual (BASE)
Queries	Complex JOINs	Simple lookups
Best For	Transactions, analytics	Scale, flexibility

5Decision Framework

Need ACID transactions?

Yes → SQLNo → NoSQL possible

Data has complex relationships?

Yes → SQLNo → Document or K-V

Need horizontal scaling?

Yes → NoSQLNo → SQL works fine

Schema changes frequently?

Yes → Document DBNo → SQL is fine

Simple key-value access?

Yes → Redis/DynamoDBNo → Consider SQL

6Key Takeaways

1SQL is ideal for structured data with relationships and ACID requirements

2NoSQL shines for scale, flexibility, and specific access patterns

3Document DBs for flexible schemas, K-V for speed, Graph for relationships

4Many modern systems use both-SQL for transactions, NoSQL for caching/scale

5Choose based on access patterns, not hype

?Quiz

1. Which database type is best for financial transactions?

2. You need to store user sessions with simple key-value access. Best choice?