DynamoDB Streams vs Kinesis: Key Differences and When to Use Each

Both DynamoDB Streams and Amazon Kinesis are AWS services for processing streaming data, but DynamoDB Streams captures changes only from DynamoDB tables, while Kinesis handles large-scale, real-time data streams from various sources. Use DynamoDB Streams for reacting to database changes and Kinesis for broader, high-throughput streaming data processing.

Quick Comparison

This table summarizes the main differences between DynamoDB Streams and Amazon Kinesis.

Feature	DynamoDB Streams	Amazon Kinesis
Data Source	Changes in DynamoDB tables only	Any streaming data source (logs, events, metrics)
Data Retention	24 hours	24 hours by default, up to 7 days
Throughput	Limited by DynamoDB table activity	High throughput, scalable shards
Use Case	React to DB changes, replication, triggers	Real-time analytics, complex event processing
Integration	Tightly integrated with DynamoDB	Standalone service, integrates with many AWS tools
Data Ordering	Ordered per partition key	Ordered per shard

Key Differences

DynamoDB Streams is a feature built into DynamoDB that captures item-level changes such as inserts, updates, and deletes. It provides a time-ordered sequence of these changes for a single table, making it ideal for triggering actions based on database events or replicating data.

In contrast, Amazon Kinesis is a standalone streaming platform designed to handle large volumes of streaming data from multiple sources. It supports multiple shards for parallel processing and longer data retention, making it suitable for real-time analytics and complex event processing beyond just database changes.

While DynamoDB Streams is limited to the scope of a single DynamoDB table and has a fixed 24-hour retention, Kinesis offers more flexibility in data sources, retention periods, and throughput scaling. Also, Kinesis requires more setup and management compared to the automatic integration of DynamoDB Streams with DynamoDB tables.

Code Comparison

Here is an example of reading records from a DynamoDB Stream using AWS SDK for Python (boto3):

python

import boto3

# Create a DynamoDB Streams client
streams_client = boto3.client('dynamodbstreams')

# Replace with your stream ARN
stream_arn = 'arn:aws:dynamodb:region:account-id:table/YourTable/stream/label'

# Get the stream's shards
shards_response = streams_client.describe_stream(StreamArn=stream_arn)
shards = shards_response['StreamDescription']['Shards']

# Get shard iterator for the first shard
shard_id = shards[0]['ShardId']
shard_iterator_response = streams_client.get_shard_iterator(
    StreamArn=stream_arn,
    ShardId=shard_id,
    ShardIteratorType='TRIM_HORIZON'
)
shard_iterator = shard_iterator_response['ShardIterator']

# Read records from the stream
records_response = streams_client.get_records(ShardIterator=shard_iterator, Limit=10)
records = records_response['Records']

for record in records:
    print(record['dynamodb'])

Output

Prints the DynamoDB item change records from the stream, showing keys like 'Keys', 'NewImage', 'OldImage', and 'SequenceNumber'.

Amazon Kinesis Equivalent

Here is an example of reading records from an Amazon Kinesis stream using AWS SDK for Python (boto3):

python

import boto3

# Create a Kinesis client
kinesis_client = boto3.client('kinesis')

# Replace with your stream name
stream_name = 'YourKinesisStream'

# Get the stream's shards
shards_response = kinesis_client.describe_stream(StreamName=stream_name)
shards = shards_response['StreamDescription']['Shards']

# Get shard iterator for the first shard
shard_id = shards[0]['ShardId']
shard_iterator_response = kinesis_client.get_shard_iterator(
    StreamName=stream_name,
    ShardId=shard_id,
    ShardIteratorType='TRIM_HORIZON'
)
shard_iterator = shard_iterator_response['ShardIterator']

# Read records from the stream
records_response = kinesis_client.get_records(ShardIterator=shard_iterator, Limit=10)
records = records_response['Records']

for record in records:
    print(record['Data'].decode('utf-8'))

Output

Prints the data payload of the first 10 records from the Kinesis stream as decoded UTF-8 strings.

When to Use Which

Choose DynamoDB Streams when you need to react to changes in your DynamoDB tables, such as triggering workflows, replicating data, or auditing changes. It is simple to use and automatically integrated with DynamoDB.

Choose Amazon Kinesis when you require a scalable, high-throughput streaming platform that can ingest data from multiple sources beyond DynamoDB. It is best for real-time analytics, complex event processing, and long-term data retention.

Key Takeaways

DynamoDB Streams captures changes only from DynamoDB tables with 24-hour retention.

Amazon Kinesis handles large-scale streaming data from various sources with flexible retention and throughput.

Use DynamoDB Streams for database-triggered workflows and Kinesis for broad real-time data processing.

DynamoDB Streams is simpler and tightly integrated; Kinesis offers more scalability and flexibility.

Code to read from both services involves getting shard iterators and fetching records using AWS SDK.