EventBridge vs SNS vs SQS

In the modern cloud-native landscape, the shift from monolithic architectures to decoupled microservices has elevated asynchronous messaging from a "nice-to-have" to a foundational requirement. As a senior architect, the most frequent question I encounter during design reviews is not whether to use an asynchronous pattern, but which AWS service should broker the communication. The choice between Amazon EventBridge, Amazon Simple Notification Service (SNS), and Amazon Simple Queue Service (SQS) often dictates the scalability, cost, and operational complexity of the entire system.

Choosing the wrong tool often leads to "architectural debt." For instance, using SQS where a pub-sub model is required leads to rigid, point-to-point integrations that are difficult to scale. Conversely, using EventBridge for high-volume, low-latency telemetry data can result in unnecessary costs and throttled throughput. Understanding the nuances of these services is critical for building resilient systems that can handle production-grade workloads.

Architecture and Core Concepts

The fundamental distinction between these services lies in their delivery model: SQS is a "pull" service (message queuing), while SNS and EventBridge are "push" services (pub-sub and event bus). In a production environment, we rarely use one in isolation. Instead, we compose them to leverage their specific strengths.

In this architecture, EventBridge acts as the central nervous system, routing events based on complex metadata patterns. SNS handles high-throughput fan-out, and SQS provides the "buffer" or load-leveling required to ensure that downstream consumers are not overwhelmed during traffic spikes.

Implementation: Multi-Service Dispatcher

To illustrate how these services interact, consider a TypeScript implementation using the AWS SDK v3. This example demonstrates how a single application might interact with all three services based on the specific requirements of the message.

import { SQSClient, SendMessageCommand } from "@aws-sdk/client-sqs";
import { SNSClient, PublishCommand } from "@aws-sdk/client-sns";
import { EventBridgeClient, PutEventsCommand } from "@aws-sdk/client-eventbridge";

const sqsClient = new SQSClient({});
const snsClient = new SNSClient({});
const ebClient = new EventBridgeClient({});

async function dispatchMessage(payload: any) {
  // 1. SQS: For direct, point-to-point processing with load leveling
  await sqsClient.send(new SendMessageCommand({
    QueueUrl: process.env.QUEUE_URL,
    MessageBody: JSON.stringify(payload),
    DelaySeconds: 0
  }));

  // 2. SNS: For high-throughput broadcast to multiple subscribers
  await snsClient.send(new PublishCommand({
    TopicArn: process.env.TOPIC_ARN,
    Message: JSON.stringify(payload),
    MessageAttributes: {
      "eventType": { DataType: "String", StringValue: "OrderCreated" }
    }
  }));

  // 3. EventBridge: For complex routing and third-party integrations
  await ebClient.send(new PutEventsCommand({
    Entries: [{
      Source: "com.mycompany.orders",
      DetailType: "OrderCreated",
      Detail: JSON.stringify(payload),
      EventBusName: "ApplicationBus"
    }]
  }));
}

In production, you would typically use PutEvents for domain events that multiple disparate teams might care about, Publish for internal high-speed notifications, and SendMessage when you have a specific worker task that needs guaranteed processing.

Best Practices and Comparison

Performance and Cost Optimization

Performance tuning requires understanding the latency trade-offs. SQS and SNS are optimized for speed and high throughput. EventBridge, while slightly slower due to its advanced rules engine, offers superior "filtering" capabilities that can save costs by preventing unnecessary Lambda invocations.

To optimize costs:

1. SQS Batching: Always use SendMessageBatch and ReceiveMessage with MaxNumberOfMessages set to 10. This reduces the number of API calls, which is the primary billing metric.
2. SNS Filtering: Use SNS filter policies to ensure consumers only receive relevant messages. This prevents paying for Lambda execution time to simply "discard" a message.
3. EventBridge Fine-tuning: Leverage the "Archive and Replay" feature instead of building custom replay logic. It is significantly cheaper and more reliable for recovering from downstream failures.

Monitoring and Production Patterns

In a production environment, visibility is paramount. You must account for partial failures and "poison pill" messages. The most robust pattern involves Dead Letter Queues (DLQs) for all three services, though their implementation differs.

For SQS, monitor the ApproximateAgeOfOldestMessage metric. A rising age indicates that your consumers are falling behind or failing. For SNS and EventBridge, focus on NumberOfNotificationsFailed and FailedInvocations. These metrics are the first indicators of permission issues or downstream service throttling.

Another critical production pattern is the "Circuit Breaker." If an SQS consumer detects that a downstream database is down, it should stop polling (or reduce concurrency) to avoid moving all messages to the DLQ prematurely.

Conclusion

The choice between EventBridge, SNS, and SQS is not about which service is "better," but which one fits the communication semantics of your architecture. SQS is your workhorse for reliable, point-to-point task processing. SNS is your high-speed broadcaster for simple fan-out scenarios. EventBridge is your sophisticated orchestrator, perfect for complex, evolving ecosystems where schema management and content-based routing are essential. By combining these services—using EventBridge for routing, SNS for scale, and SQS for durability—you create a resilient, event-driven architecture capable of handling enterprise-scale demands.

References:

• https://docs.aws.amazon.com/eventbridge/latest/userguide/eb-what-is.html
• https://docs.aws.amazon.com/sns/latest/dg/welcome.html
• https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/welcome.html
• https://aws.amazon.com/builders-library/architecting-next-generation-event-driven-systems/