DynamoDB Capacity Modes

Capacity Modes Overview

At its core, capacity modes is about doing one thing well inside your DynamoDB project. Once you understand the pattern, you can apply it consistently across features and teams.

Good capacity modes pays off across the whole codebase: fewer surprises, easier testing, and smoother onboarding. The snippet below is a solid starting point.

import { DynamoDBClient } from '@aws-sdk/client-dynamodb';
import { DynamoDBDocumentClient, GetCommand, PutCommand } from '@aws-sdk/lib-dynamodb';

const client = new DynamoDBClient({});
const docClient = DynamoDBDocumentClient.from(client);

// reuse docClient across the module for efficient, typed access
await docClient.send(new PutCommand({ TableName: 'Orders', Item: { pk: '1' } }));

The DynamoDBDocumentClient maps plain JavaScript objects to DynamoDB item format for you.

Capacity Modes Example

import { DynamoDBClient } from '@aws-sdk/client-dynamodb';
import { DynamoDBDocumentClient } from '@aws-sdk/lib-dynamodb';

const docClient = DynamoDBDocumentClient.from(new DynamoDBClient({}));
// docClient.send(new PutCommand(...)) etc.

• Start from a minimal Capacity Modes example and grow it only as needed.
• Keep configuration explicit so Capacity Modes behaves the same in every environment.
• Name things clearly so teammates understand your Capacity Modes at a glance.
• Add tests around Capacity Modes early to lock in expected behaviour.

Amazon DynamoDB Cheatsheet

Handy DynamoDB (AWS SDK v3) reference related to capacity modes.

How Capacity Modes Works in DynamoDB

Capacity Modes builds on DynamoDB's key-value and document model, where every item lives in a partition chosen by its partition key and is optionally ordered by a sort key.

The DynamoDBDocumentClient maps plain JavaScript objects to DynamoDB item format for you.

• Design access patterns first, then model keys around them.
• Prefer Query over Scan for predictable performance.
• Use expressions to read and write only what you need.
• Keep items small and avoid hot partitions.

Practical Guidance for Capacity Modes

In production, capacity modes should be cost-aware and resilient. Right-size capacity, handle throttling with retries, and lean on indexes to support your query patterns.

Common Mistakes

• Skipping error handling and edge cases when wiring up capacity modes.
• Leaving capacity modes untested, so regressions slip into production.
• Over-engineering capacity modes before you actually need the extra flexibility.
• Ignoring documentation, which makes capacity modes hard for the next developer to change.

Key Takeaways

• Capacity Modes is a core part of working effectively with DynamoDB.
• Start small and keep capacity modes focused on a single responsibility.
• Apply consistent patterns so capacity modes scales across your project.
• Test and document capacity modes to keep it maintainable over time.