SQL vs NoSQL Databases

SQL Databases (Relational)

Characteristics

• Structure: Fixed schema with tables, rows, columns
• ACID Properties: Atomicity, Consistency, Isolation, Durability
• Query Language: Standard SQL
• Relationships: Foreign keys, joins

Examples

• MySQL
• PostgreSQL
• Oracle
• SQL Server
• SQLite

Advantages

• Data Consistency: ACID compliance
• Complex Queries: Joins, aggregations
• Mature Ecosystem: Tools, documentation
• Standardized: SQL is universal

Use Cases

• Financial systems
• E-commerce platforms
• ERP systems
• Applications requiring complex transactions

NoSQL Databases (Non-Relational)

Types

1. Document Databases

• Examples: MongoDB, CouchDB
• Structure: JSON-like documents
• Use Case: Content management, catalogs

2. Key-Value Stores

• Examples: Redis, DynamoDB
• Structure: Simple key-value pairs
• Use Case: Caching, session storage

3. Column-Family

• Examples: Cassandra, HBase
• Structure: Column families
• Use Case: Time-series data, IoT

4. Graph Databases

• Examples: Neo4j, Amazon Neptune
• Structure: Nodes and edges
• Use Case: Social networks, recommendations

Advantages

• Scalability: Horizontal scaling
• Flexibility: Dynamic schema
• Performance: Optimized for specific use cases
• Big Data: Handle large volumes efficiently

Disadvantages

• Consistency: Eventually consistent
• Limited Queries: No standard query language
• Less Mature: Fewer tools and expertise

When to Choose SQL

1. ACID Compliance Required

   • Financial transactions
   • Critical data integrity

2. Complex Relationships

   • Multiple entity relationships
   • Complex queries with joins

3. Mature Application

   • Well-defined requirements
   • Stable schema

4. Reporting and Analytics

   • Business intelligence
   • Complex aggregations

When to Choose NoSQL

1. Rapid Development

   • Frequent schema changes
   • Agile development

2. Horizontal Scaling

   • High traffic applications
   • Global distribution

3. Unstructured Data

   • Varying data formats
   • JSON, XML documents

4. Real-time Applications

   • Gaming leaderboards
   • IoT data collection

Hybrid Approaches

Polyglot Persistence

• Use different databases for different purposes
• SQL for transactions, NoSQL for caching
• Choose best tool for each job

Example Architecture

User Management → PostgreSQL (ACID compliance)
Product Catalog → MongoDB (flexible schema)
Session Storage → Redis (fast key-value)
Recommendations → Neo4j (graph relationships)

Migration Considerations

SQL to NoSQL

• Denormalization: Flatten relationships
• Data Modeling: Think in collections/documents
• Query Patterns: Design for access patterns

NoSQL to SQL

• Schema Design: Define relationships
• Normalization: Reduce data redundancy
• Constraints: Add data validation rules

Performance Comparison