Conditional Put

Conditional Put Overview

Conditional Put lets you structure DynamoDB work so it stays readable, testable, and easy to scale. Instead of ad-hoc code, you follow a clear pattern that other developers can recognise immediately.

The key is to keep conditional put focused and predictable. Start from the minimal example here, then layer in only the complexity your feature actually needs.

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

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

await docClient.send(new PutCommand({
  TableName: 'Orders',
  Item: { pk: 'ORDER#123', sk: 'META', total: 42, status: 'NEW' },
  ConditionExpression: 'attribute_not_exists(pk)',
}));

PutCommand writes an item; the condition expression prevents overwriting an existing one.

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

Amazon DynamoDB Cheatsheet

Handy DynamoDB (AWS SDK v3) reference related to conditional put.

How Conditional Put Works in DynamoDB

Conditional Put 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.

PutCommand writes an item; the condition expression prevents overwriting an existing one.

• 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 Conditional Put

In production, conditional put 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 conditional put.
• Leaving conditional put untested, so regressions slip into production.
• Over-engineering conditional put before you actually need the extra flexibility.
• Ignoring documentation, which makes conditional put hard for the next developer to change.

Key Takeaways

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