Query vs Scan

Query vs Scan sits at the heart of scan operations in DynamoDB. This guide walks through the concept step by step, with examples, a cheatsheet, and common mistakes to avoid.

Query vs Scan Overview

Query vs Scan 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 query vs scan 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, 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.

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

Amazon DynamoDB Cheatsheet

Handy DynamoDB (AWS SDK v3) reference related to query vs scan.

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 Query vs Scan Works in DynamoDB

Query vs Scan 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 Query vs Scan

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

Key Takeaways

Query vs Scan is a core part of working effectively with DynamoDB.
Start small and keep query vs scan focused on a single responsibility.
Apply consistent patterns so query vs scan scales across your project.
Test and document query vs scan to keep it maintainable over time.

Pro Tip

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