aws-messaging-and-streaming

To choose between SQS, SNS, and EventBridge, evaluate your workload's latency, throughput, and ordering requirements. SQS handles decoupled queueing, SNS enables pub/sub fan-out, and EventBridge routes structured events to multiple targets.

The best AWS streaming pattern for high-throughput data ingestion uses Kinesis or MSK. Kinesis Data Streams handles real-time data processing, while MSK provides managed Apache Kafka clusters for persistent streaming workloads.

Use Kinesis Firehose instead of Kinesis Data Streams when you need to deliver streaming data directly to destinations like S3 or Redshift without writing custom consumer applications. Firehose manages delivery and transformation automatically.

To configure an AWS messaging service for event-driven workloads, select a pattern based on retention and integration needs, then outline the service configuration steps. Use SQS for point-to-point queues or SNS for broadcast fan-out.

Tradeoffs between AWS messaging and streaming services involve latency, message ordering, and retention. Messaging services like SQS offer simple decoupling, while streaming services like Kinesis provide ordered data processing and longer retention.

You need Amazon MQ if your workload requires existing standard APIs like JMS or AMQP protocol compatibility. For new cloud-native applications, serverless services like SQS, SNS, and EventBridge are generally recommended over MQ.