LSI Projections

LSI Projections Overview

At its core, lsi projections 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 lsi projections 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, QueryCommand } from '@aws-sdk/lib-dynamodb';

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

const { Items } = await docClient.send(new QueryCommand({
  TableName: 'Orders',
  KeyConditionExpression: 'pk = :pk AND begins_with(sk, :prefix)',
  ExpressionAttributeValues: { ':pk': 'USER#42', ':prefix': 'ORDER#' },
  Limit: 25,
}));

QueryCommand reads a partition efficiently using key conditions; add IndexName for a GSI.

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

Amazon DynamoDB Cheatsheet

Handy DynamoDB (AWS SDK v3) reference related to lsi projections.

How LSI Projections Works in DynamoDB

LSI Projections 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.

QueryCommand reads a partition efficiently using key conditions; add IndexName for a GSI.

• 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 LSI Projections

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

Key Takeaways

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