Kinesis Data Stream vs Firehose

Overview

Kinesis Data Stream

Amazon Kinesis Data Streams is a scalable and durable real-time data streaming service that can continuously capture gigabytes of data per second from hundreds of thousands of sources. It's designed to enable real-time analytics and insights from streaming data, such as logs, social media feeds, and IoT telemetry.

Kinesis Firehose

Amazon Kinesis Data Firehose is a fully managed service for delivering real-time streaming data directly to destinations like Amazon S3, Redshift, Elasticsearch, and Splunk. It's primarily used for simpler data delivery needs without the need for custom processing.

Key Differences

1. Data Processing:

   • Kinesis Data Streams: Offers the capability for custom data processing using Kinesis Data Analytics or external processing frameworks.
   • Kinesis Firehose: Primarily focuses on data delivery, but allows basic transformations and format conversions.

2. Management:

   • Kinesis Data Streams: Requires manual scaling and shard management.
   • Kinesis Firehose: Fully managed, automatic scaling.

3. Data Storage:

   • Kinesis Data Streams: Stores data for 24 hours by default, extendable up to 7 days.
   • Kinesis Firehose: Does not store data, directly delivers to specified destinations.

4. Integrations:

   • Kinesis Data Streams: Requires integration with other AWS services for data storage or analytics.
   • Kinesis Firehose: Integrates directly with services like S3, Redshift, and Elasticsearch for immediate data delivery.

5. Use Cases:

   • Kinesis Data Streams: Best for applications requiring real-time analytics, complex processing, or temporary data storage.
   • Kinesis Firehose: Ideal for simple, real-time data delivery needs without the necessity of storage or complex processing.

6. Pricing:

   • Kinesis Data Streams: Charged based on the number of shards and data retention period.
   • Kinesis Firehose: Charged based on the amount of data ingested and transformed.

Practical Use Cases

• Kinesis Data Streams:

  • Real-time monitoring and analytics for large-scale applications.
  • Complex event processing in financial trading platforms.
  • Aggregating and analyzing high-volume IoT device data.

• Kinesis Firehose:

  • Streaming log data directly to S3 for later analysis.
  • Feeding data into Redshift for business intelligence purposes.
  • Sending real-time application logs to Elasticsearch for operational insights.

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Conclusion

Kinesis Data Streams and Kinesis Firehose are both powerful services for handling real-time streaming data. The choice between them largely depends on the specific requirements of data processing, management, and delivery. Kinesis Data Streams offers more flexibility and control for complex processing needs, whereas Kinesis Firehose provides a simpler, fully managed solution for direct data delivery.