DynamoDB with AWS SAM

with AWS SAM sits at the heart of serverless applications in DynamoDB. This guide walks through the concept step by step, with examples, a cheatsheet, and common mistakes to avoid.

with AWS SAM Overview

with AWS SAM is a building block you will reach for often in DynamoDB. It keeps related logic together and makes your intent obvious to reviewers and future maintainers.

When you learn with aws sam properly, you avoid the guesswork that leads to bugs and rework. The example below shows the shape you will use in most real DynamoDB projects.

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.

with AWS SAM 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 with AWS SAM example and grow it only as needed.
Keep configuration explicit so with AWS SAM behaves the same in every environment.
Name things clearly so teammates understand your with AWS SAM at a glance.
Add tests around with AWS SAM early to lock in expected behaviour.

Amazon DynamoDB Cheatsheet

Handy DynamoDB (AWS SDK v3) reference related to with aws sam.

Operation	Command	Purpose
Create/replace	`PutCommand`	Write an item
Read one	`GetCommand`	Fetch by primary key
Update	`UpdateCommand`	Modify attributes
Delete	`DeleteCommand`	Remove an item
Query	`QueryCommand`	Efficient key-based read
Scan	`ScanCommand`	Full-table read (avoid)
Transaction	`TransactWriteCommand`	Atomic multi-item writes

How with AWS SAM Works in DynamoDB

with AWS SAM 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 with AWS SAM

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

Concern	Recommendation
Performance	Query by key; avoid table scans
Cost	Use on-demand or right-sized provisioned capacity
Modeling	Design for known access patterns
Reliability	Retry throttled requests with backoff

Common Mistakes

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

Key Takeaways

with AWS SAM is a core part of working effectively with DynamoDB.
Start small and keep with aws sam focused on a single responsibility.
Apply consistent patterns so with aws sam scales across your project.
Test and document with aws sam to keep it maintainable over time.

Pro Tip

Pair with aws sam with automated tests from day one. It is far cheaper to catch DynamoDB regressions in CI than in production.