Alexis Kestler
Dear reader,
Welcome to my comprehensive guide on the top message brokers used in modern applications today. As an experienced data analyst and technology enthusiast, I‘m excited to walk you through everything you need to know about these critical tools for enabling communication between network services and applications.
Get ready to learn how message brokers work, their key benefits, and detailed profiles of the most popular options available. By the end, you‘ll have all the information you need to select the right message broker for your needs. Let‘s get started!
What Exactly is a Message Broker?
Simply put, a message broker is software that enables different applications and services to communicate by passing messages between them. It serves as a translation layer that converts messages from one system‘s messaging protocol to another.
This allows services written in different languages and running on different platforms to exchange information seamlessly. The broker handles all the complex work of reliably routing and delivering messages behind the scenes.
According to IBM, global message broker software revenue reached nearly $700 million in 2021 and is projected to grow approximately 11% annually through 2026. This growth reflects the pivotal role message brokers play in modern distributed architectures.
Key Capabilities
Message brokers unlock several key capabilities:
- Messaging – Send, receive, and queue messages between endpoints
- Routing – Intelligently distribute messages between applications
- Transformation – Convert message formats between different protocols
- Security – Encrypt messages and authenticate client applications
- Monitoring – Track message flow for analytics and troubleshooting
- Storage – Persist messages reliably for deferred processing
- Management – Administer brokers and message queues
How Do Message Brokers Work?
Now that you know what message brokers do, let‘s explore how they work under the hood. Here are the key components and concepts:
Message Producers and Consumers
A producerapplication generates messages and delivers them to the broker. The broker then routes and delivers these messages to relevant consumer applications.
Producers and consumers are fully decoupled – the producer simply publishes messages without knowledge of what systems will consume them.
Message Queues
The broker stores messages destined for consumers in message queues. Queues provide reliable buffering, ordering, and retry capabilities. There are two fundamental queue types:
Point-to-Point – Messages are delivered to a single consumer. Useful for workflows and guaranteed delivery.
Publish-Subscribe – Messages are broadcast to multiple subscribed consumers. Useful for notifications and events.
Queues decouple message production from consumption, allowing systems to communicate asynchronously at different speeds.
Exchanges and Bindings
In pub-sub models, exchanges route messages from producers to queues using message attributes and queue bindings. Bindings link queues to precise message "topics" they are interested in receiving.
For example, a "log event" exchange could route log messages to a "log archival" queue based on a binding.
Message Formats
Messages have a format defined by a messaging protocol, such as AMQP, MQTT, STOMP, or Kafka‘s native protocol. Message brokers translate between protocols using adapters or plugins. Common translations include AMQP to/from MQTT and Kafka.
Persistence and Reliability
Message brokers use persistence techniques like journalling or data replication to prevent message loss. Messages stored in queues are durable until intentionally removed by consuming applications.
Brokers also support features like acknowledgements and redelivery attempts to ensure guaranteed message processing.
Key Benefits of Message Brokers
Now that you understand the basics of how brokers work, let‘s explore the benefits they provide:
1. Decouple Systems and Scale Independently
Message brokers allow producer and consumer systems to evolve and scale independently. Applications connect through a common integration layer versus direct point-to-point links.
This prevents changes to one system from cascading to others. It also enables independent scaling – consume more messages simply by adding consumers.
According to a Copper report, 78% of developers cite decoupled architecture as a key benefit of message brokers.
2. Reduce Complexity Through Asynchronous Communication
Synchronous communication requires consumers to be online and ready to receive messages. Message brokers enable asynchronous communication using durable message queues.
Producers can rapidly publish messages without waiting for a response. Consumers can be offline yet still process messages later at their own pace. This asynchronous model dramatically simplifies distributed system design.
3. Improve Reliability with Guaranteed Delivery
By persisting messages and retrying failed deliveries, brokers provide guaranteed at-least-once or exactly-once delivery. Lost messages are extremely rare since the broker handles retries automatically.
For example, RabbitMQ offers multiple acknowledged modes:
- At least once delivery (default)
- Exactly once delivery with publisher confirms
- Exactly once processing with consumer ACKs
4. Translate Between Messaging Protocols
An IoT solution may need to bridge MQTT devices, Kafka data pipelines, and AMQP business services. Message brokers provide adapters to translate between protocols – a single broker can speak many languages!
Popular translations include AMQP ↔ MQTT, AMQP ↔ Kafka, and MQTT ↔ Kafka. This prevents vendor lock-in.
According to G2 Crowd, protocol adaptability and translation capabilities are the #2 evaluation criteria users have for message brokers, following closely behind reliability.
5. Improve Performance and Reduce Load
Brokers temporarily store and route messages quickly using techniques like batching and caching to improve throughput. Consumers can scale out across threads and processes to parallelize message processing.
This load balancing reduces congestion and improves overall system performance. Message distribution patterns can reduce loads on busy services by fanning out requests.
6. Enable Event-Driven Architectures
Message brokers are ideal for event-driven system designs. Producers publish event messages asynchronously. Stateless consumers receive only the event data they need versus sharing databases.
This runs faster and scales better than synchronous polling or REST designs. Message brokers have catalyzed the growth of event-driven architectures over the past decade.
Top Message Brokers for Modern Applications
Now that you understand the value message brokers provide, let‘s explore the leading options available today:
1. RabbitMQ
Overview – RabbitMQ is an extremely popular open source broker that supports multiple messaging protocols and client libraries. It‘s known for high reliability, performance, interoperability, and ease of use.
Details
- Created in 2007, written in Erlang
- Installable on-prem or in cloud
- Supports AMQP, MQTT, STOMP protocols
- Persistent queuing, exchange-to-queue binding
- Distributed clusters for high availability
- Easy admin UI, management API, CLI tool
- Client libraries for Java, .NET, Python, JS, Go, etc.
Use Cases
- General purpose messaging backbone
- Event streaming and data pipelines
- Job queues for microservices
- Point of sale and financial systems
- Gaming and mobile apps
Why Choose RabbitMQ?
RabbitMQ strikes a great balance being easy to use while still offering enterprise features. It has a proven track record with tremendous community support. The versatile messaging and queueing models handle a wide range of scenarios.
2. Apache Kafka
Overview – Kafka focuses on high-performance data streaming and processing. It uses a distributed pub-sub model uniquely tailored for very high message throughput.
Details
- Created by LinkedIn, open sourced in 2011
- Written in Java and Scala
- Uses ZooKeeper for coordination
- Topic-based message streaming
- Specialized logger and disk structures
- Horizontal scaling through partitioning
- Integrates with data systems via Kafka Connect
Use Cases
- Streaming data pipelines
- Messaging for microservices
- Metrics and log aggregation
- Commit logs for fast DB replication
- Stream processing apps (with Kafka Streams API)
Why Choose Kafka?
Kafka offers unmatched throughput performance combined with strong ordering guarantees. Data streams stay available in Kafka for days or weeks, enabling complex event processing. Kafka Streams makes it easy to transform streams with embedded event-at-a-time processing.
3. ActiveMQ
Overview – A veteran open source message broker written in Java that‘s hugely popular in the enterprise. It offers traditional enterprise messaging capabilities.
Details
- Created in 2004, stewarded by the Apache Foundation
- Supports AMQP, MQTT, STOMP, OpenWire
- Queuing, message groups, transactions
- Cross-language clients for Java, C#, Python, etc.
- Integrates with Java EE and Spring apps
- Extensible through a mature plugin ecosystem
- Available embedded or standalone server
Use Cases
- Traditional service bus for Java EE
- Messaging provider for app servers
- Protocols adapters and data transformations
- Connection layer for microservices
Why Choose ActiveMQ?
ActiveMQ is proven, time-tested, full of features, and integrates beautifully with Java backends. It‘s less specialized than some brokers which provides flexibility. The embedded broker makes it easy to add messaging to Java apps.
4. AWS SQS
Overview – A fully-managed message queuing service from AWS. Simple Queue Service (SQS) is used widely with other AWS services and provides reliable, scalable queues.
Details
- Launch instantly, no servers to manage
- Serves billions of messages per month
- Integrates natively with other AWS resources
- Scales transparently without configuration
- Encryption, access controls, auditing
- Delay queues, message timers, retries
- Integrates using AWS SDKs
- Pay only for what you use, starts at $0.40 per million requests
Use Cases
- Cloud-native apps on AWS
- Decouple and scale microservices
- Distribute load and enable resilience
- Drive serverless workflows
- Coordinate distributed computing jobs
Why Choose SQS?
SQS delivers highly scalable, reliable message queuing without operating your own environment. It‘s secure, integrates seamlessly with other AWS services, and pricing is cost efficient.
5. Solace PubSub+
Overview – An enterprise-grade message broker optimized for ultra-high performance, security, and global scale. It offers advanced queuing, publish-subscribe, request-reply patterns, and data streaming in a single platform.
Details
- Supports AMQP, JMS, MQTT, REST
- Guaranteed messaging with publish-subscribe, queuing, and request-reply
- Hardware and software appliances available
- Can process millions of messages per second
- Client support for C, Java, .NET, mobile, and more
- Built-in data streaming, transformation, storage
- Deploys on-prem, cloud, hybrid environments
- Integration services and support packages available
Use Cases
- High performance event streaming
- Distributed data replication
- Real-time service integration
-Bridging consumer IoT devices - Financial transaction processing
Why Choose Solace PubSub+?
Solace PubSub+ provides unmatched performance at scale and robust enterprise capabilities like guaranteed delivery. It offers comprehensive messaging patterns and protocols with the flexibility to deploy on-premises, natively within clouds, or across complex hybrid environments.
6. NATS
Overview – An open-source messaging system designed for high-performance cloud native applications. It focuses on security, simplicity, performance and scalability.
Details
- Created by Synadia in 2015
- Lightweight Golang implementation
- Auto-pruning topic subscriptions
- At-most-once delivery model
- Pluggable authentication and authorization
- APIs for Go, Java, Node.js, C, and more
- Used by many cloud providers incl. Pivotal Cloud Foundry
- Can process millions of messages per second
Use Cases
- Lightweight communication between microservices
- Internal distributed data streams
- Integration hub for cloud native apps
- Remote procedure calls (gRPC support)
- IoT networks
Why Choose NATS?
NATS delivers exceptional performance, scale, and resiliency. Its simple API promotes easy adoption and fast development cycles. NATS is well suited for integrating modern applications deployed in cloud environments.
Key Criteria When Choosing a Broker
With so many options, how do you select the right message broker? Here are key criteria to consider for your use case:
- Protocols – Does the broker support the messaging protocols you need?
- Performance – Does it handle your throughput and response time needs?
- Reliability – Does the broker provide strong delivery guarantees?
- Persistence – Does it support durable message storage until processed?
- Security – Does it meet your encryption, access control and audit requirements?
- Scalability – Can it scale to your expected message volumes as needed?
- Ecosystem – Are there client libraries for your app environments and languages?
- Administration – Is the broker easy to setup, configure, monitor and manage?
- Cost – Are the licensing or hosting costs acceptable?
Think about your functional and non-functional requirements. Prioritize the criteria above accordingly to pick the right message broker for your applications!
Start Simplifying Your Architecture with Message Brokers
I hope this guide provided you a helpful overview of message brokers and how they enable communication between services in distributed architectures. The leading options available today like Kafka, RabbitMQ, and ActiveMQ are proven solutions.
As applications become increasingly decoupled into microservices and transition to the cloud, message brokers will play an ever more critical role. They reduce complexity, improve reliability, and unlock scalability across your environment.
Whether you‘re decomposing monoliths or developing new cloud-native apps, introducing a message broker can simplify your architecture. Are you ready to reap the benefits? Let me know if you have any other questions!
