Rabbitmq on AWS EKS vs SQS hosting cost comparison

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Short comparison of the RabbitMQ on AWS EKS and AWS SQS

  • features and costs.

Flying invelopes in the cloud

TL;DR: RabbitMQ on AWS EKS (Elastic Kubernetes Service) generally costs more than using AWS SQS.

Short overview

RabbitMQ on EKS, SQS, and Kinesis offer different messaging solutions with varying cost implications. Kinesis is generally the most cost-effective for high-throughput real-time data streams, while SQS is a suitable option for standard message queuing needs, and RabbitMQ on EKS provides more flexibility but at a potentially higher operational cost. Here’s a breakdown of the key considerations:

Kinesis

Strengths:

  • Cost-effective for high-throughput data streams: Kinesis is designed for real-time data processing, making it very efficient for large volumes of data.

Fully managed service: AWS manages the infrastructure, reducing operational overhead. Scalable: Kinesis can handle large volumes of data and scale to meet changing needs.

Cost:

Shard-based pricing: Kinesis pricing is based on the number of shards (processing units) and the amount of data processed.

Lower costs for high-throughput data streams: For applications involving high-throughput data, Kinesis can be significantly cheaper than SQS or RabbitMQ.

Use Cases:

  • IoT data streams: Kinesis is ideal for processing sensor data from IoT devices.

Real-time analytics: It can be used for real-time analytics of event data. Application logging: Kinesis can handle large volumes of application logs.

SQS

Strengths:

  • Fully managed service: AWS manages the infrastructure, simplifying operations.

Decoupled communication: SQS enables decoupled communication between microservices and other components. Standard message queuing: SQS is well-suited for traditional message queuing needs.

Cost:

Pricing based on requests and data transfer: SQS charges based on the number of requests and the amount of data transferred.

Potentially higher cost for high-throughput: SQS might be more expensive than Kinesis for applications with high-throughput requirements.

Use Cases:

  • Microservices architectures: SQS is a popular choice for enabling communication between microservices.

Background processing: It can be used for background tasks that do not require immediate responses. Asynchronous event handling: SQS can be used to handle events asynchronously.

RabbitMQ on EKS:

Strengths:

Flexible and customizable: RabbitMQ offers a wide range of features and configurations, enabling it to handle complex messaging scenarios.

Open-source and community-supported: RabbitMQ is an open-source project with a large community, providing ample support and resources. Multiple protocols: RabbitMQ supports multiple messaging protocols, making it compatible with various systems.

Cost:

Operational cost: Running RabbitMQ on EKS incurs costs for EKS cluster management, instance maintenance, and other operational overhead.

Potential for higher cost: The cost can be higher compared to SQS or Kinesis depending on the workload and the size of the cluster.

Use Cases:

  • Complex messaging scenarios: RabbitMQ is well-suited for handling complex routing and filtering needs.

Multi-protocol environments: It can support multiple messaging protocols. Hybrid cloud architectures: RabbitMQ can be used in hybrid cloud environments where on-premise and cloud-based systems need to communicate.

In summary:

  • Choose Kinesis for high-throughput real-time data streams.
  • Choose SQS for standard message queuing and microservices.
  • Choose RabbitMQ on EKS for complex messaging scenarios, multi-protocol environments, and when you need more control.

Cost Comparison: RabbitMQ on EKS vs Amazon SQS

RabbitMQ on EKS (Amazon Elastic Kubernetes Service)

  • Running RabbitMQ on EKS means you are responsible for provisioning, scaling, and maintaining both the Kubernetes cluster and the RabbitMQ deployment.
  • Costs include:
    • EKS cluster management fee (currently $0.10 per hour, or about $72 per month per cluster, as of 2025).
    • EC2 instances for worker nodes (cost varies by instance type and number of nodes).
    • EBS volumes for RabbitMQ data (charged per GB per month).
    • Networking and data transfer costs.
    • Operational overhead: patching, monitoring, scaling, and troubleshooting.
  • For managed RabbitMQ, such as Amazon MQ for RabbitMQ, a typical 3-node mq.m5.large cluster with 200GB storage costs about $702.82 per month in the US East (N. Virginia) region, including both instance and storage charges. Running your own RabbitMQ on EKS could be somewhat cheaper if you optimize resources, but you must factor in the operational effort and potential for under/over-provisioning.

Amazon SQS (Simple Queue Service)

  • SQS is a fully managed service with no infrastructure to manage.
  • Pricing is usage-based:
    • First 1 million requests per month are free.
    • After that, Standard queues cost $0.40 per million requests; FIFO queues cost $0.50 per million requests.
    • No charges for storage or idle queues.
    • Data transfer in is free; data transfer out is charged, but transfers to other AWS services in the same region are free.
  • No operational overhead; scaling, availability, and durability are handled by AWS.

Summary Table

Aspect RabbitMQ on EKS Amazon SQS
Pricing Model Infrastructure + Ops + Storage Pay-per-request
Example Cost ~$700/month (managed 3-node) $0.40–$0.50 per million requests
Free Tier None (except EC2/EKS free tier) 1 million requests/month
Scalability Manual/auto-scaling required Fully managed, scales automatically
Maintenance You manage everything AWS manages everything

In Conclusion

  • RabbitMQ on EKS can be more cost-effective at very high volumes if you optimize your infrastructure, but comes with significant operational complexity and ongoing management costs.
  • Amazon SQS is typically much cheaper and simpler for most workloads, especially at low to moderate volumes, due to its pay-per-use model and lack of operational overhead.
  • For most cloud-native applications, SQS is the preferred choice unless you have specific requirements (e.g., advanced messaging patterns or on-premises compatibility) that RabbitMQ provides.

In summary, SQS is generally more cost-effective and operationally efficient for most AWS workloads, while RabbitMQ on EKS may be justified only if you have unique requirements or existing RabbitMQ expertise.

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