AWS DynamoDB Patterns: Building Scalable NoSQL Applications

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.

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

1. Data Modeling

   • Design for specific access patterns
   • Use composite sort keys
   • Implement single-table design
   • Minimize secondary indexes

2. Performance

   • Use DAX for caching
   • Implement auto scaling
   • Choose appropriate partition keys
   • Use batch operations

3. Cost Optimization

   • Monitor and optimize capacity
   • Use on-demand capacity wisely
   • Implement TTL for data cleanup
   • Optimize item size

4. Security

   • Use IAM roles and policies
   • Encrypt data at rest
   • Implement VPC endpoints
   • Monitor with CloudTrail

References

1. DynamoDB Documentation
2. Best Practices
3. Security
4. Performance