- Event-driven architecture: EventBridge is a serverless event bus service that makes it easy to connect applications using data from your own applications, integrated AWS services, or Software-as-a-Service (SaaS) applications.
- Routing and Filtering: It routes events from various sources to specific targets based on filtering rules. You can set up complex event patterns and rules to trigger specific actions.
- Fully managed: No infrastructure to manage, and it automatically scales with your usage.
- Event sources: It natively integrates with many AWS services (e.g., S3, Lambda, EC2), SaaS providers, and custom applications.
- Event-Driven Microservices: Connect microservices by routing events between them without needing the services to be tightly coupled.
- Real-time processing: Automatically trigger workflows, serverless functions, or notifications in response to certain events.
- Integration with third-party SaaS: Easily ingest events from third-party applications like Zendesk, Shopify, or PagerDuty and route them to AWS services.
- Event Pattern Filtering: Define complex rules to match and filter events.
- Schema Registry: Automatically discover event schemas and manage them centrally.
- Reliability: Built-in fault tolerance and reliability.
- Security: Supports encryption, fine-grained access control (IAM), and audit logging.
- Data streaming: Kinesis is designed for processing and analyzing real-time, continuous streams of data at scale. It can ingest large volumes of data and allows applications to consume and process it in real-time.
- Components: Kinesis Data Streams: Ingests large streams of data and allows consumers to process them in parallel. Kinesis Data Firehose: Delivers data to destinations like S3, Redshift, or Elasticsearch with minimal setup. Kinesis Data Analytics: Enables real-time processing and analysis of streaming data using SQL.
- Real-time analytics: Monitor and analyze log data, clickstreams, social media feeds, IoT data, etc., in real time.
- Data Ingestion: Capture and store massive amounts of data (like log data) for later processing and analysis.
- Real-time dashboards: Power live dashboards with continuously updating metrics and information.
- High throughput: Can process gigabytes of data per second from hundreds of thousands of sources.
- Real-time processing: Low latency processing of data streams.
- Integration: Easily integrates with other AWS services (Lambda, S3, Redshift, etc.) for data processing, storage, and analysis.
- Scalability: Automatically scales to accommodate growing data streams.
- Durability: Stores data across multiple availability zones for fault tolerance.
- Event Type: EventBridge: Primarily focuses on events (discrete occurrences) such as API calls, changes in state, etc. Kinesis: Focuses on continuous data streams like log data, IoT data, etc.
- Processing Model: EventBridge: Routes events based on rules; typically event-driven with a focus on triggering actions. Kinesis: Provides a pipeline for real-time data ingestion and processing, ideal for big data and analytics.
- Scale: EventBridge: Suitable for event-driven architectures with potentially lower volumes of events. Kinesis: Designed for high-throughput, real-time data streaming applications.
- Latency: EventBridge: Low latency for triggering events and workflows. Kinesis: It also has low latency but is optimized for streaming data processing rather than discrete events.
- Use EventBridge if you need to build event-driven architectures, integrate with SaaS services, or route events with complex filtering to trigger workflows or serverless functions.
- Use Kinesis if you need to ingest, process, and analyze large volumes of streaming data in real-time, like logs, telemetry data, or financial transactions.
They can also be used together, where EventBridge triggers events based on certain criteria, and Kinesis handles the real-time data processing.
