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Kinesis vs EventBridge

Overview​

Kinesis​

Amazon Kinesis is a set of services for real-time data streaming and analytics. It includes Kinesis Data Streams for collecting and processing large streams of data records, and Kinesis Data Firehose for loading streaming data into AWS data stores. It's designed for high-throughput, scalable, and real-time processing of streaming data.

EventBridge​

Amazon EventBridge is a serverless event bus service that connects application data, integrated Software-as-a-Service (SaaS) applications, and AWS services. It enables applications to communicate with each other using events, which are data points reflecting changes in your applications or services.

Key Differences​

  1. Primary Function:

    • Kinesis: Focused on real-time data streaming and processing.
    • EventBridge: Centers around event-driven architectures, routing events between AWS services, custom applications, and third-party SaaS applications.

  2. Data Handling:

    • Kinesis: Handles high-volume, sequential data streams.
    • EventBridge: Deals with discrete events, typically in a JSON format.

  3. Integration and Target Services:

    • Kinesis: Integrates well with other AWS analytics services like AWS Lambda, Redshift, and Elasticsearch.
    • EventBridge: Can route events to AWS Lambda, EC2, SNS, SQS, and many other AWS services, as well as third-party service integrators.

  4. Use Cases:

    • Kinesis: Ideal for real-time analytics, log and data feed intake, and processing large-scale streaming data.
    • EventBridge: Best suited for building decoupled, event-driven architectures and reacting to state changes in your applications or services.

  5. Scalability:

    • Kinesis: Requires managing stream capacities, though it can handle very high throughput.
    • EventBridge: Fully managed and serverless, scales automatically without any need to manage resources.

  6. Pricing:

    • Kinesis: Charges based on the volume of data transferred and processed, and shard hours.
    • EventBridge: Pricing is based on the number of events published to the bus and the number of invocations of targets.

Practical Use Cases​

  • Kinesis:

    • Streaming data processing for real-time analytics (e.g., financial transaction analysis).
    • Collecting and analyzing IoT sensor data in real-time.
    • Processing and ingesting large-scale log data streams.

  • EventBridge:

    • Orchestrating microservices by triggering actions in response to events.
    • Automating workflows in response to SaaS application events.
    • Integrating and routing events from AWS services to custom applications or third-party services.
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Conclusion​

Kinesis is ideal for applications that require real-time processing and analysis of large streams of data, offering high throughput and integration with AWS analytics tools. EventBridge, on the other hand, is better suited for creating event-driven applications and workflows, offering a serverless event bus that connects various AWS services and SaaS applications. The choice depends on the specific architecture and requirements of your application.