DynamoDB patterns¶

DynamoDB patterns are proven solutions to common data modeling challenges. Understanding and applying these patterns is essential for building efficient, scalable applications with DynamoDB.

Why patterns matter¶

DynamoDB is fundamentally different from relational databases. Success requires understanding patterns that leverage DynamoDB's strengths:

• Performance: Patterns optimize for single-digit millisecond latency
• Cost: Efficient patterns minimize read/write capacity consumption
• Scalability: Proper patterns distribute load and avoid hot partitions
• Flexibility: Patterns enable complex queries without joins

Pattern categories¶

Key design patterns¶

These patterns focus on how to structure your partition and sort keys:

• Entity Keys - Type-safe entity identification with prefixed keys
• Composite Keys - Combining multiple attributes into keys
• Multi-Attribute Keys - Advanced composite key management

Data organization patterns¶

These patterns help organize related data for efficient access:

• Time-Series - Storing and querying time-ordered data
• Hierarchical - Modeling parent-child relationships
• Adjacency List - Modeling graph relationships

Performance patterns¶

These patterns optimize for performance and scalability:

• Hot Partition Distribution - Distributing load across partitions
• Sparse Indexes - Creating efficient secondary indexes

Choosing the right pattern¶

Pattern selection guide¶

For simple entity storage: - Start with Entity Keys - Add Composite Keys for relationships

For time-based data: - Use Time-Series pattern - Consider Sparse Indexes for filtering

For hierarchical data: - Use Hierarchical pattern - Or Adjacency List for graphs

For high-traffic scenarios: - Apply Hot Partition Distribution - Use Multi-Attribute Keys for flexibility

Pattern structure¶

Each pattern page includes:

• What: Clear explanation of the pattern
• Why: Benefits and use cases
• When: Guidance on when to apply it
• How: Implementation with code examples
• Visual Diagrams: Clear visual representations
• Related Patterns: Connections to other patterns

Learning path¶

1. Start with basics: Understand Entity Keys first
2. Add complexity: Learn Composite Keys
3. Explore relationships: Study Hierarchical and Adjacency List
4. Optimize performance: Apply Hot Partition Distribution
5. Master advanced: Use Multi-Attribute Keys

Additional resources¶

• Best Practices - Optimization techniques
• Anti-Patterns - Common mistakes to avoid
• Usage Guides - Feature-specific guides
• Examples - Complete working examples

Pattern implementation¶

All patterns are implemented in the @ddb-lib/core package with helper functions that make applying these patterns straightforward and type-safe.

import { PatternHelpers } from '@ddb-lib/core'

// Entity keys
const userKey = PatternHelpers.entityKey('USER', '123')

// Composite keys
const orderKey = PatternHelpers.compositeKey(['ORDER', userId, orderId])

// Distributed keys
const shardedKey = PatternHelpers.distributedKey('ACTIVE_USERS', 10)

Start exploring patterns to build efficient DynamoDB applications!