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A message queueing service is a message-oriented middleware or MOM deployed in a compute cloud using software as a service model. Service subscribers access queues and or topics to exchange data using point-to-point or publish and subscribe patterns.
It's important to differentiate between event-driven and message-driven (aka queue driven) services: Event-driven services (e.g. AWS SNS) are decoupled from their consumers. Whereas queue / message driven services (e.g. AWS SQS) are coupled with their consumers.[1]
Message queues can be a good buffer to handle spiky workloads but they have a finite capacity. According to Gregor Hohpe, message queues require proper mechanisms (aka flow controls) to avoid filling the queue beyond its manageable capacity and to keep the system stable.[2]
Ordering Guarantees in Message Queues
Amazon SQS FIFO and Azure Service Bus sessions are queue-based messaging systems that provide ordering guarantees within a message group or session attempt but do not necessarily guarantee ordered delivery in cases of retries or failures. In SQS FIFO, messages in the same message group are processed in order, with subsequent messages held until the preceding message is successfully processed or moved to the dead-letter queue (DLQ). Once a message is placed in the DLQ, it is no longer retried, creating a gap in the sequence. However, the remaining messages continue to be delivered in order.[3][4][5]
Azure Service Bus sessions function similarly by maintaining ordering within a session, provided a single consumer processes messages sequentially. The implementation differs from SQS FIFO but follows the same fundamental ordering principle. [6][7]
In contrast, Apache Kafka is a distributed log-based messaging system that guarantees ordering within individual partitions rather than across the entire topic. Unlike queue-based systems, Kafka retains messages in a durable, append-only log, allowing multiple consumers to read at different offsets. Kafka uses manual offset management, giving consumers control over retries and failure handling. If a consumer fails to process a message, it can delay committing the offset, preventing further progress in that partition while other partitions remain unaffected. This partition-based design enables fault isolation and parallel processing while allowing ordering to be maintained within partitions, depending on consumer handling. [8]
Vendors
- Apache Kafka
- [9] Apache Kafka is a distributed system consisting of servers that store and forward messages between producer client and consumer applications.
- IBM MQ
- [10] IBM MQ offers a managed service that can be used on IBM Cloud and Amazon Web Services.
- Microsoft Azure Service Bus
- [11] Service Bus offers queues, topics & subscriptions, and rules/actions in order to support publish-subscribe, temporal decoupling, and load balancing scenarios. Azure Service Bus is built on AMQP allowing any existing AMQP 1.0 client stack to interact with Service Bus directly or via existing .Net, Java, Node, and Python clients. Standard and Premium tiers allow for pay as you go or isolated resources at massive scale.
- Oracle Messaging Cloud Service
- [12] This service provides a messaging solution for applications for asynchronous communication and is influenced by the Java Message Service (JMS) API specification. Any application platform that understands HTTP can also use Oracle Messaging Cloud Service through the REST interface. For Java applications, Oracle Messaging Cloud Service provides a Java library that implements and extends the JMS 1.1 interface. The Java library implements the JMS API by acting as a client of the REST API.
- Amazon Simple Queue Service
- [13] Supports messages natively up to 256K, or up to 2GB by transmitting payload via S3. Highly scalable, durable and resilient. Provides loose-FIFO and 'at least once' delivery in order to provide massive scale. Supports REST API and optional Java Message Service client. Low latency. Utilizes Amazon Web Services.
- IronMQ
- [14] Supports messages up to 64k; guarantees order; guarantees once only delivery; no delays retrieving messages. Supports REST API and beanstalkd open source protocol. Runs on multiple clouds including AWS and Rackspace. Scaling must be managed by user.
- RabbitMQ
- [15] RabbitMQ is a reliable and mature messaging and streaming broker, which is easy to deploy on cloud environments, on-premises, and on your local machine. Supports AMQP, STOMP, MQTT
- StormMQ
- [16] Open platform supports messages up to 50Mb. Uses AMQP to avoid vendor lock-in and provide language neutrality. Locate-It Option allows customers to audit the location of their data at all times and satisfy data protection principles.
- AnypointMQ
- [17] An enterprise multi-tenant, cloud messaging service that performs advanced asynchronous messaging scenarios between applications. Anypoint MQ is fully integrated with Anypoint Platform, offering role based access control, client application management, and connectors.
See also
References
- ^ Chandrasekaran, Premanand; Krishnan, Karthik; Ford, Neal; Byars, Brandon; Buijze, Allard (2022). Domain-Driven Design with Java - A Practitioner's Guide. Packt Publishing. ISBN 9781800564763.
- ^ Hohpe, Gregor. Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions. Addison-Wesley Professional. ISBN 978-0321200686.
- ^ "FIFO queue delivery logic in Amazon SQS - Amazon Simple Queue Service". docs.aws.amazon.com. Retrieved 2025-08-07.
- ^ "Using dead-letter queues in Amazon SQS - Amazon Simple Queue Service". docs.aws.amazon.com. Retrieved 2025-08-07.
- ^ "Amazon SQS FIFO queues - Amazon Simple Queue Service". docs.aws.amazon.com. Retrieved 2025-08-07.
- ^ spelluru (2025-08-07). "Azure Service Bus message sessions - Azure Service Bus". learn.microsoft.com. Retrieved 2025-08-07.
- ^ spelluru (2025-08-07). "Service Bus dead-letter queues - Azure Service Bus". learn.microsoft.com. Retrieved 2025-08-07.
- ^ Narkhede, Neha; Shapira, Gwen; Palino, Todd (2017). Kafka: the definitive guide: real-time data and stream processing at scale (First edition ed.). Sebastopol, CA: O'Reilly Media. ISBN 978-1-4919-3616-0. OCLC 933521388.
{{cite book}}:|edition=has extra text (help) - ^ "Intro to Kafka". Apache Kafka. 2025-08-07.
- ^ "IBM MQ on Cloud". IBM. 2025-08-07.
- ^ "Microsoft Azure Service Bus". 2025-08-07.
- ^ "Using Oracle Messaging Cloud Service". Oracle Help Center. Retrieved 2025-08-07.
- ^ "Amazon Simple Queue Service (API Version 2025-08-07)". 2025-08-07.
- ^ "IronMQ". iron.io. Archived from the original on 2025-08-07. Retrieved 2025-08-07.
ties distributed systems together by providing a reliable way to communicate between services and components. Highly available, persistent by design, with best-effort one-time delivery, IronMQ is the most industrial strength, cloud-native solution for modern application architecture.
- ^ "RabbitMQ". Retrieved 2025-08-07.
- ^ "StormMQ". 2025-08-07. Archived from the original on 2025-08-07.
- ^ "AnypointMQ". 2025-08-07.