DynamoDB doesn’t have a traditional SQL-style LIMIT clause. Instead, it offers the ability to limit the number of items returned in a query or scan using the Limit parameter. This is extremely useful for pagination, performance, and cost control.

In this guide, we’ll walk through how to use Limit effectively in DynamoDB with Python and Boto3.

Table of Contents

1. Understanding LIMIT in DynamoDB

2. Prerequisites

3. Using Limit in a scan() Operation

4. Using Limit in a query() Operation

5. Pagination with LastEvaluatedKey

6. Complete Example with Pagination

7. Tips and Best Practices

8. Common Pitfalls

9. Conclusion

1. Understanding LIMIT in DynamoDB

• Limit controls the maximum number of items returned by a query() or scan() request.

• It does not guarantee total number of results unless you check for LastEvaluatedKey.

• Can be used for pagination, preview results, or testing performance.

Important: DynamoDB internally pages results in 1MB chunks. If a Limit is higher than what fits in 1MB, the request may still be paged.

⚙️ 2. Prerequisites

Make sure you have:

• A DynamoDB table (e.g., Users)

• Python and boto3 installed:

pip install boto3

• AWS credentials configured via aws configure

Sample table: Users
Primary Key: user_id (partition key)

3. Using Limit in a scan() Operation

The scan() method reads every item in the table but can be limited using the Limit parameter.

import boto3

dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table('Users')

response = table.scan(Limit=5)
items = response['Items']

print("First 5 items:")
for item in items:
    print(item)

⚠️ Use scan() with caution for large tables — it’s expensive and slow.

4. Using Limit in a query() Operation

The query() method retrieves items that match a partition key, and can also be limited.

response = table.query(
    KeyConditionExpression=boto3.dynamodb.conditions.Key('user_id').eq('001'),
    Limit=3
)

items = response['Items']
print("First 3 items for user_id=001:")
for item in items:
    print(item)

5. Pagination with LastEvaluatedKey

DynamoDB won’t return more than your Limit, or beyond 1MB of data. To fetch the next "page", you must use the LastEvaluatedKey.

Example:

response = table.scan(Limit=5)
items = response['Items']
last_key = response.get('LastEvaluatedKey')

while last_key:
    response = table.scan(Limit=5, ExclusiveStartKey=last_key)
    items.extend(response['Items'])
    last_key = response.get('LastEvaluatedKey')

6. Complete Example with Pagination Function

import boto3

def scan_with_limit(table_name, limit):
    dynamodb = boto3.resource('dynamodb')
    table = dynamodb.Table(table_name)

    response = table.scan(Limit=limit)
    items = response['Items']
    last_key = response.get('LastEvaluatedKey')

    print(f"Fetched {len(items)} items:")
    for item in items:
        print(item)

    if last_key:
        print("\nMore items available. Use `ExclusiveStartKey` to continue.\n")
    else:
        print("\nEnd of data reached.")

# Run it
scan_with_limit('Users', 5)

7. Tips and Best Practices

⚠️ 8. Common Pitfalls

✅ 9. Conclusion

The Limit parameter in DynamoDB is essential when you need to:

• Page through large datasets

• Avoid high read costs

• Fetch previews of data

When paired with LastEvaluatedKey, Limit lets you efficiently and safely paginate through tables, especially in applications like admin dashboards, APIs, or reports.