AWS
AWS DynamoDB Patterns: Building Scalable NoSQL Applications
Learn essential patterns and best practices for designing and implementing scalable applications using Amazon DynamoDB, including data modeling, access patterns, and optimization strategies
February 25, 2024
DevHub Team
2 min read
Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. This guide explores common patterns and best practices for building efficient applications with DynamoDB.
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graph TB
subgraph DataModel["Data Modeling"]
direction TB
Keys["Key Design"]
Schema["Schema Design"]
Patterns["Access Patterns"]
end
subgraph Operations["Data Operations"]
direction TB
Write["Write Operations"]
Stream["Stream Processing"]
Query["Query Patterns"]
end
subgraph Features["Advanced Features"]
direction TB
subgraph Performance["Performance"]
direction LR
DAX["DAX"]
AutoScale["Auto Scaling"]
end
subgraph Security["Security"]
direction LR
IAM["IAM"]
KMS["KMS"]
VPC["VPC Endpoints"]
end
end
DataModel --> Operations
Operations --> Features
classDef modelNode fill:#FF9900,stroke:#232F3E,color:#232F3E,stroke-width:2px,font-weight:bold
classDef operationNode fill:#232F3E,stroke:#232F3E,color:#FFFFFF,stroke-width:2px,font-weight:bold
classDef featureNode fill:#147EB4,stroke:#232F3E,color:#FFFFFF,stroke-width:2px,font-weight:bold
classDef groupStyle fill:transparent,stroke:#232F3E,stroke-width:2px,color:#232F3E,font-weight:bold
class Keys,Schema,Patterns modelNode
class Write,Stream,Query operationNode
class DAX,AutoScale,IAM,KMS,VPC featureNode
class DataModel,Operations,Features,Performance,Security groupStyle
Data Modeling Patterns
1. Single Table Design
interface OrderItem { PK: string; // ORDER#<orderId> SK: string; // METADATA#<timestamp> GSI1PK: string; // CUSTOMER#<customerId> GSI1SK: string; // ORDER#<status>#<timestamp> orderId: string; customerId: string; status: string; amount: number; createdAt: string; }
2. Write Operations
const AWS = require('aws-sdk'); const dynamodb = new AWS.DynamoDB.DocumentClient(); async function getCustomerOrders(customerId, startDate, endDate) { const params = { TableName: 'Orders', KeyConditionExpression: 'PK = :pk AND SK BETWEEN :start AND :end', ExpressionAttributeValues: { ':pk': `CUSTOMER#${customerId}`, ':start': `ORDER#${startDate}`, ':end': `ORDER#${endDate}` } }; return await dynamodb.query(params).promise(); }
Best Practices
-
Data Modeling
- Design for specific access patterns
- Use composite sort keys
- Implement single-table design
- Minimize secondary indexes
-
Performance
- Use DAX for caching
- Implement auto scaling
- Choose appropriate partition keys
- Use batch operations
-
Cost Optimization
- Monitor and optimize capacity
- Use on-demand capacity wisely
- Implement TTL for data cleanup
- Optimize item size
-
Security
- Use IAM roles and policies
- Encrypt data at rest
- Implement VPC endpoints
- Monitor with CloudTrail
References
DynamoDB
NoSQL
Database
Performance
