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DynamoDB best practices

Building efficient and cost-effective DynamoDB applications requires understanding and applying proven best practices. This section covers essential patterns and techniques that will help you optimize performance, reduce costs, and build scalable systems.

Why best practices matter

DynamoDB is a powerful database, but its performance and cost characteristics differ significantly from traditional relational databases. Following best practices ensures:

  • Optimal performance: Achieve consistent low-latency responses even at scale
  • Cost efficiency: Minimize read and write capacity consumption
  • Scalability: Design systems that scale seamlessly with your application
  • Maintainability: Create data models that are easy to understand and evolve

Core best practices

query vs scan

Always prefer Query operations over Scan operations. Queries are efficient and cost-effective, while scans examine every item in your table regardless of what you're looking for.

Impact: Queries can be 100x faster and cheaper than scans on large tables.

projection expressions

Use projection expressions to retrieve only the attributes you need. This reduces data transfer, lowers costs, and improves performance.

Impact: Can reduce read capacity consumption by 50-90% depending on item size.

batch operations

Use batch operations (BatchGetItem, BatchWriteItem) when working with multiple items. The library automatically handles chunking and retries.

Impact: Up to 10x throughput improvement compared to individual operations.

conditional writes

Use conditional expressions to ensure data integrity and implement optimistic locking. This prevents race conditions and data corruption.

Impact: Eliminates the need for read-before-write patterns, improving performance and reducing costs.

capacity planning

Understand your access patterns and plan capacity accordingly. Use on-demand mode for unpredictable workloads and provisioned mode for steady, predictable traffic.

Impact: Can reduce costs by 50% or more with proper capacity planning.

key design

Design your partition and sort keys to support your access patterns efficiently. Good key design is fundamental to DynamoDB performance.

Impact: Proper key design enables efficient queries and prevents hot partitions.

How to use this section

Each best practice page includes:

  • Clear explanation: What the practice is and why it matters
  • Visual comparisons: Side-by-side examples of good vs. poor implementations
  • Code examples: Working code showing the correct approach
  • Performance metrics: Real-world impact on performance and cost
  • When to apply: Guidance on when the practice is most important

Getting started

If you're new to DynamoDB, start with these foundational practices:

  1. Query vs scan - The most important performance optimization
  2. Key design - Foundation for all other optimizations
  3. Projection expressions - Easy wins for cost reduction

For more advanced optimization:

  1. Batch operations - Maximize throughput
  2. Conditional writes - Ensure data integrity
  3. Capacity planning - Optimize costs
  • Patterns - Common DynamoDB design patterns
  • Anti-Patterns - Common mistakes to avoid
  • Guides - Detailed usage guides for library features

Monitoring your application

The @ddb-lib/stats package helps you identify opportunities to apply these best practices:

import { StatsCollector, RecommendationEngine } from '@ddb-lib/stats'

const stats = new StatsCollector()
const recommendations = new RecommendationEngine(stats)

// Get recommendations based on your usage patterns
const suggestions = recommendations.getRecommendations()

for (const suggestion of suggestions) {
  console.log(`${suggestion.type}: ${suggestion.message}`)
  console.log(`Potential impact: ${suggestion.impact}`)
}

The recommendation engine will suggest which best practices to apply based on your actual usage patterns.