EventBridge vs Apache Kafka

From an application perspective the key benefits are:

EventBridge Benefits

• Near-zero application code needed for AWS service integration - just configure rules and targets

• Built-in error handling and dead letter queues require minimal custom code

• Event filtering and transformation happens at the service level, keeping application code clean

• Easy schema validation and enforcement without extra application logic

• Simple JSON-based event patterns make event routing logic straightforward

• Application can leverage built-in retry policies without implementing them

Kafka Benefits

• Applications can replay messages from any point in time (great for recovery/debugging)

• Stronger ordering guarantees for messages within partitions

• Applications can scale horizontally by adding more consumers to a consumer group

• Custom serialization formats beyond JSON can be used efficiently

• Applications can implement backpressure mechanisms for better flow control

• Multiple applications can process the same events independently (consumer groups)

• Fine-grained control over message delivery semantics (at-least-once, exactly-once)

Feature	Amazon EventBridge	Apache Kafka
Infrastructure Management	Fully managed by AWS	Self-managed or using managed services (MSK, Confluent)
Maximum Throughput	Up to 10,000 events/second per account	Millions of events per second
Latency	Milliseconds	Sub-millisecond
Message Retention	24 hours by default	Configurable, can retain indefinitely
Message Size	Maximum 256KB	Configurable, default 1MB
Ordering	Best-effort ordering	Strict ordering within partitions
Replay Capability	Limited (archive/replay feature)	Full replay from any offset
Development Complexity	Low - simple JSON rules	Higher - requires more configuration
Event Filtering	Rich pattern matching built-in	Client-side filtering
AWS Integration	Native with 100+ AWS services	Requires custom integration
Scalability Model	Automatic	Manual partition management
Consumer Groups	Not applicable	Built-in consumer group concept
Dead Letter Queues	Built-in support	Manual implementation
Schema Registry	Built-in schema registry	Separate service required
Error Handling	Automatic retries and DLQ	Manual implementation needed
Cost Model	Pay per event	Infrastructure + data transfer
Security	IAM integration, encryption at rest	Manual security configuration
Monitoring	CloudWatch integration	Custom monitoring setup
Cross-Region	Built-in global endpoints	Manual replication setup
Backpressure Handling	Not available	Built-in protocol support
Protocol Support	HTTP/HTTPS	Multiple protocols (PLAINTEXT, SSL, SASL)
Client Libraries	AWS SDKs	Multiple language clients
Use Case Focus	Serverless event routing	High-throughput stream processing

Does Event Bridge have a concept of partitions, similar to kafka?

EventBridge does not have a direct equivalent to Kafka's partitions. Instead, EventBridge uses different concepts for message distribution:

1. Event Buses - These are the streams that collect events, but they don't have internal partitioning like Kafka

2. Rules - These determine where events go, but don't provide the same ordering guarantees as Kafka partitions

"EventBridge processes events at least once, which means that a single event might be delivered to a target more than once. However, EventBridge attempts to deliver events in order to targets, but does not guarantee event ordering."

EventBridge Pipes provides "ordered event delivery within a pipe", but this is still different from Kafka's partition model where you can have multiple partitions with strict ordering within each partition.