Best Event Brokers

Guide to Event Brokers

An event broker is a system that facilitates communication between different components or services in a distributed system by managing the flow of events. Events typically represent significant occurrences or changes in state, such as user actions, system updates, or messages. Event brokers play a crucial role in decoupling producers and consumers of events, allowing them to operate independently without being directly connected. By serving as an intermediary, an event broker ensures that events are efficiently transmitted and processed across different applications, platforms, or microservices.

These brokers enable asynchronous communication, which means that producers of events do not need to wait for consumers to process them. This decouples the timing between services, improving scalability and fault tolerance. Event brokers can handle large volumes of events in real-time, ensuring that data flows smoothly across the system, even when there are spikes in traffic. Additionally, event brokers often provide features such as event filtering, prioritization, and persistence, ensuring that critical events are not lost and are processed in the correct order.

Event brokers are widely used in modern architectures such as microservices, serverless systems, and event-driven architectures. Technologies like Apache Kafka, RabbitMQ, and Amazon EventBridge are popular examples of event brokers. By using these systems, organizations can design highly scalable, efficient, and flexible applications. Event brokers also simplify debugging and monitoring, as they often come with tools that allow users to track and visualize event flows, which helps in identifying performance bottlenecks or failures in the system.

What Features Do Event Brokers Provide?

• Event Routing: Event brokers route events from producers to appropriate consumers. Routing ensures that events are sent to the right destination based on rules, topic subscriptions, or filtering criteria. This feature ensures that consumers receive relevant events without having to query or monitor all event sources manually, thereby reducing unnecessary network traffic and improving system efficiency.
• Message Persistence: Event brokers offer message persistence by storing events temporarily on disk or in memory until they are successfully consumed or processed. This helps in guaranteeing message delivery even if consumers are temporarily unavailable. Ensures that no events are lost in case of system failures or downtime, providing reliability and fault tolerance.
• Decoupling of Producers and Consumers: By using an event broker, producers and consumers are decoupled. Producers do not need to know about the consumers, and vice versa. The broker acts as an intermediary between them. This decoupling promotes flexibility and scalability in the system. It allows changes to be made to producers or consumers without affecting the other components, which is essential for evolving systems.
• Event Filtering: Event brokers can filter events based on predefined criteria or consumer preferences. For example, a consumer might only be interested in specific types of events based on content, topic, or other attributes. Helps reduce the volume of unnecessary events sent to consumers, improving the overall system's performance and ensuring consumers only get the events they need.
• Event Transformation: Some event brokers can transform the format of the event data before it is sent to consumers. This transformation could include altering data structures, encoding formats, or aggregating information. Facilitates integration between systems with different data formats or protocols. Consumers do not need to perform these transformations themselves, reducing their complexity and workload.
• Reliability & Delivery Guarantees: Event brokers provide various delivery guarantees such as "at-most-once," "at-least-once," and "exactly-once" delivery, which define how events should be handled in terms of duplication, acknowledgment, and fault tolerance. These guarantees are essential for ensuring that events are not lost or processed incorrectly, which is critical in applications like financial transactions or real-time analytics.
• Asynchronous Communication: Event brokers facilitate asynchronous communication, meaning that producers can send events without waiting for an immediate response from consumers. Enhances performance by allowing producers to continue their work without delay. Consumers, on the other hand, can process events independently at their own pace, reducing bottlenecks.
• Scalability: Event brokers are designed to scale horizontally, meaning they can handle an increasing number of events and consumers by distributing the load across multiple broker instances or clusters. Provides the ability to scale an event-driven system to handle high volumes of events, ensuring that performance and reliability are maintained as demand grows.
• Event Replay: Event brokers can support event replay, allowing consumers to reprocess past events. This can be useful for debugging, data recovery, or when a consumer needs to catch up after being offline for a period of time. Helps ensure that consumers can process events even if they missed them initially, enabling systems to recover from failures or perform historical analysis.
• High Availability: Many event brokers are designed to be highly available, with failover mechanisms that ensure service continuity even in the event of hardware failures or network partitions. High availability is critical for mission-critical applications where downtime can lead to loss of data or system disruption.
• Event Ordering: Event brokers can maintain the order of events when delivering them to consumers. This is particularly important in scenarios where events need to be processed in the exact order in which they were generated. Ensures the correct sequence of operations, which is necessary in applications where event order is crucial, such as financial transactions or multi-step workflows.
• Security and Access Control: Event brokers often include mechanisms for securing event data and controlling access to events. This can include encryption, authentication, and authorization to ensure that only authorized users or systems can produce or consume events. Protects sensitive data and ensures that only authorized parties can participate in the event-driven system, mitigating security risks and unauthorized access.
• Dead Letter Queue (DLQ): Event brokers may include a dead letter queue, where events that cannot be delivered or processed are placed for later inspection and handling. This helps to prevent message loss and allows for troubleshooting and error handling. A DLQ ensures that messages that could not be successfully processed are not lost and can be reviewed or retried, preventing potential data loss or system inconsistencies.
• Real-Time Processing: Event brokers enable real-time event streaming, allowing events to be processed as soon as they are generated. This is particularly useful in applications requiring low-latency processing, such as stock trading systems, IoT applications, and real-time analytics. Real-time processing allows for quick decision-making and immediate reactions to events, which is essential for systems where time-sensitive actions are critical.
• Multiple Protocol Support: Many event brokers support a variety of communication protocols such as AMQP, MQTT, Kafka, or HTTP, allowing them to interface with different systems and applications, regardless of their communication method. Ensures compatibility across diverse platforms and applications, enabling easier integration in heterogeneous environments.
• Monitoring and Metrics: Event brokers often provide monitoring capabilities, allowing administrators to track key performance metrics like event throughput, processing time, and delivery success rates. These tools may include dashboards, alerts, and logs. Monitoring enables administrators to track the health of the event-driven system, identify performance bottlenecks, and ensure that the broker is operating efficiently.

What Are the Different Types of Event Brokers?

• Message Brokers: Message brokers are event brokers that handle the routing of messages between producers and consumers. They facilitate the exchange of data by decoupling message producers from consumers, ensuring that messages are delivered to the correct recipients.
• Streaming Event Brokers: Streaming event brokers are designed to handle high-throughput, real-time streams of events. These brokers enable the processing of continuous event streams and allow consumers to subscribe to them for real-time updates.
• Event Queues: Event queues manage the orderly delivery of events to consumers by placing events in a queue. Consumers pull events from the queue in a sequential manner, ensuring that events are processed in the order they are received.
• Publish-Subscribe Event Brokers: In the publish-subscribe model, event brokers enable producers (publishers) to broadcast events to multiple consumers (subscribers). Consumers subscribe to specific event types and receive events of interest.
• Event-Driven Architectures (EDA) Brokers: These event brokers focus on enabling event-driven architectures, where the communication between services is based on events rather than direct calls.
• Log-Based Event Brokers: Log-based event brokers manage the persistence and retrieval of event logs. These brokers maintain an immutable log of events that can be read by consumers in real time or for historical analysis.
• Brokerless Event Systems: In brokerless event systems, event communication happens directly between producers and consumers without the need for a centralized broker. Event handling is decentralized, and producers push events directly to consumers.
• Hybrid Event Brokers: Hybrid event brokers combine the features of different types of event brokers, such as message queuing and streaming, to provide flexibility in event handling.
• Transactional Event Brokers: Transactional event brokers ensure that events are processed within the context of a transaction, which provides guarantees about the consistency and reliability of event delivery.
• Cloud-Native Event Brokers: Cloud-native event brokers are designed specifically for environments built around cloud infrastructures. They are highly scalable and resilient, supporting dynamic service discovery and auto-scaling.

What Are the Benefits Provided by Event Brokers?

• Decoupling of Services: Event brokers help decouple services in a system by providing a central platform where events are published and consumed. Producers of events (publishers) and consumers (subscribers) do not need to be directly aware of each other’s existence. This decoupling reduces the complexity of interactions between components. Services can evolve, scale, and fail independently without affecting the rest of the system.
• Scalability: Event brokers enable systems to scale effectively. Since services are loosely coupled, they can be scaled independently based on demand. As traffic or the volume of events increases, new consumers can be added without altering the producers, ensuring horizontal scalability and efficient resource utilization.
• Asynchronous Communication: Event brokers allow for asynchronous communication between services. Events are sent without requiring immediate responses from the recipients. This enables non-blocking operations, which improves performance, reduces latency, and makes systems more responsive. Consumers can process events at their own pace, leading to better handling of spikes in load.
• Fault Tolerance and Resilience: Most event brokers provide built-in mechanisms for handling failures, such as message retries, acknowledgments, and durable message storage. This makes the system more resilient to failures. If a service is temporarily unavailable or crashes, events are not lost and can be processed once the service is back online. This ensures high availability and continuity of operations.
• Event Persistence and Replayability: Event brokers often support the ability to persist events for later consumption or replay, even if a consumer service is temporarily unavailable. This persistence feature allows historical event data to be accessed at any time, enabling debugging, auditing, and replaying events to update the system's state or recover from failures.
• Real-time Data Processing: Event brokers provide a mechanism for streaming data in real-time, meaning services can react immediately to changes in the system or environment. This is particularly beneficial in systems requiring fast decision-making or live data analysis, such as financial platforms, sensor networks, or monitoring applications.
• Flexibility in Event Handling: Event brokers support various event processing models, such as event filtering, transformation, and aggregation, which allow complex event handling. Services can subscribe to specific types of events and handle them accordingly, which provides a high level of flexibility. Different services can react to a single event in different ways, making the architecture versatile and adaptive.
• Integration with Diverse Systems: Event brokers act as a mediator between heterogeneous systems, enabling them to communicate even if they are built on different technologies or run in different environments. This integration capability is essential in modern microservice architectures, where each service may use different frameworks, programming languages, or data storage systems.
• Load Balancing: Event brokers can distribute events across multiple consumers in a balanced way, ensuring that no single service becomes a bottleneck. This automatic load balancing improves resource utilization and enhances the performance of the system by ensuring even distribution of tasks among consumers.
• Improved System Observability: Event brokers can help track the flow of events through a system, providing insights into the system’s behavior, performance, and issues. With this visibility, developers can monitor event delivery, measure latency, and detect anomalies in real-time. It also aids in troubleshooting, system optimization, and identifying potential bottlenecks.
• Event-Driven Architecture Support: Event brokers support event-driven architecture, where services react to events instead of polling or querying other services for information. This allows for more efficient systems since services only act when they are triggered by relevant events, reducing unnecessary network calls and resource consumption.
• Cost Efficiency: By enabling decoupled, asynchronous communication and optimizing resource allocation, event brokers can help reduce overhead and infrastructure costs. As services are only active when needed, system resources such as CPU, memory, and bandwidth are used more efficiently. This can translate into lower operating costs, especially in cloud environments where resources are billed based on usage.
• Improved User Experience: With event brokers, services can respond faster to user actions or system events, enabling near-instantaneous feedback to users. This is crucial in scenarios like real-time notifications, chat applications, and live updates, where users expect fast, seamless interactions without delays.
• Streamlining Complex Workflows: Event brokers can orchestrate complex workflows where different services are triggered by events in a specific order, ensuring that tasks are performed in the right sequence. This helps in managing complex business processes or long-running workflows, ensuring that each step is completed in the correct order and preventing bottlenecks or errors in the workflow.
• Security and Access Control: Event brokers often offer advanced security features such as encryption, authentication, and authorization for event publishers and consumers. These security measures ensure that sensitive data is protected during transmission and that only authorized services have access to specific events or topics.
• Event Versioning: Many event brokers allow the versioning of events, meaning new versions of events can be introduced without breaking existing consumers. This ensures backward compatibility and minimizes the impact of changes in the system, allowing for smooth updates and the continuous evolution of the architecture.

What Types of Users Use Event Brokers?

• Software Developers: Software developers often rely on event brokers to facilitate asynchronous communication between distributed systems, microservices, and various application components. They use event brokers to decouple components, allowing them to communicate via events rather than direct API calls, which improves system reliability and scalability. Developers use event brokers to implement event-driven architectures and handle complex workflows involving multiple services or systems.
• DevOps Engineers: DevOps engineers leverage event brokers to automate and manage the flow of information between different systems, especially in large-scale, distributed environments. They use event brokers for monitoring, logging, and triggering events in response to system changes, ensuring that various components of the system can react and adapt quickly. Event brokers are often central to managing the infrastructure as code, enabling efficient monitoring, scaling, and fault tolerance.
• System Architects: System architects utilize event brokers as part of their strategy to design and build scalable, resilient, and loosely coupled systems. They often design architectures that use event brokers to handle the communication between microservices, third-party systems, and data pipelines. Event brokers play a crucial role in enabling event-driven architectures and ensuring the smooth flow of data between different parts of the system.
• Business Analysts: Business analysts use event brokers indirectly by gathering insights from the data flowing through event-driven systems. They focus on identifying key business events that drive operations, such as customer actions or system alerts. By collaborating with developers and engineers, they help define event schemas and use event-driven data to analyze system behavior and make data-driven decisions that can improve operational efficiency and customer experiences.
• Product Managers: Product managers use event brokers as part of their strategy to ensure that their products interact effectively with other products, services, or platforms. They collaborate with engineering teams to define key events that drive product features and customer interactions. Event brokers allow product managers to ensure that product functionality is well-integrated with backend systems, APIs, and other services while supporting features like real-time notifications and event-driven workflows.
• Data Engineers: Data engineers are responsible for managing and processing data at scale, and they often work with event brokers to manage real-time data streams. They use event brokers to ingest, process, and store streaming data from multiple sources. Event brokers help data engineers implement real-time data pipelines, manage ETL (extract, transform, load) processes, and integrate data sources into data lakes, ensuring that business intelligence and analytics systems can work with up-to-date information.
• Operations Engineers: Operations engineers use event brokers to monitor and manage the health of the systems in real-time. They rely on event brokers to capture system health events, alert on potential issues, and trigger automated remediation processes in response to certain events. Event brokers enable them to automate incident response, track performance metrics, and manage system state, ensuring uptime and efficiency in production environments.
• Security Engineers: Security engineers utilize event brokers to detect and respond to security threats in real-time. By collecting and processing security-related events such as login attempts, system changes, or data access, security engineers can trigger automated responses or generate alerts when suspicious activities occur. Event brokers facilitate the integration of security monitoring tools and help provide comprehensive logs and events for compliance and auditing purposes.
• Customer Support Teams: Customer support teams indirectly benefit from event brokers by having access to real-time events and data that inform them of customer issues or incidents. For instance, event brokers can be used to send alerts or notifications regarding system outages, new tickets, or the status of ongoing issues. By integrating event-driven systems into their workflows, customer support teams can respond more quickly to customer queries and provide a more seamless service experience.
• Business Operations Teams: Business operations teams use event brokers to enhance workflow automation and streamline processes across various business departments. For example, they may implement event-driven systems to trigger actions across systems like CRM, ERP, or inventory management in response to certain business events (such as order placement or inventory restocking). Event brokers ensure that these systems remain synchronized and that business processes are efficient and responsive to changing conditions.
• Third-Party Service Integrators: Third-party service integrators, such as vendors or consultants, leverage event brokers to enable communication between their clients' systems and external platforms or APIs. These integrators design solutions that connect different services and data sources, ensuring that relevant events trigger the appropriate actions in the target systems. For instance, they may use event brokers to connect payment gateways, marketing tools, or supply chain management systems to streamline operations for their clients.
• IoT Engineers and Teams: Internet of Things (IoT) engineers use event brokers to handle the large volume of real-time events generated by IoT devices. These events might represent sensor readings, device status changes, or commands sent to IoT devices. Event brokers help IoT teams scale their systems to manage device data effectively, allowing for real-time processing and the triggering of actions based on events such as temperature changes, motion detection, or device malfunctions.
• Data Scientists: Data scientists benefit from event brokers by analyzing real-time data streams and historical events to identify trends, anomalies, and patterns. They use event brokers to gather data from different sources in real-time, which allows them to build predictive models and make data-driven recommendations. Event-driven architectures powered by event brokers also allow them to train and update models more frequently with new, up-to-date information.
• Marketing Teams: Marketing teams use event brokers to implement real-time campaigns, customer engagement, and personalization. Event brokers allow them to track user interactions, such as website visits, product purchases, or email opens, and trigger marketing actions in real-time (e.g., sending personalized recommendations or offers). This allows for dynamic, event-driven marketing automation and improved customer engagement.
• Chief Information Officers (CIOs) and CTOs: CIOs and CTOs are responsible for making strategic decisions regarding technology infrastructure and architecture. They use event brokers to support digital transformation, improve system reliability, and ensure that their organizations can scale efficiently. By adopting event-driven architectures, they enable their teams to innovate and maintain flexible, responsive systems that can adapt to changing business needs and emerging technologies.

How Much Do Event Brokers Cost?

The cost of event brokers can vary widely depending on several factors, including the size of the organization, the volume of events to be processed, and the complexity of the system required. For small to mid-sized businesses, event broker solutions might be available on a subscription basis, with pricing starting at a few hundred to several thousand dollars per month. Typically, these offerings are scaled based on usage, such as the number of events processed per second or the number of endpoints integrated into the system. Many platforms also offer different pricing tiers, with entry-level solutions suitable for startups and more advanced packages tailored for enterprise-level use.

For larger enterprises or highly specialized use cases, the costs can be much higher. Custom or on-premise event brokers, which offer greater control and scalability, often involve significant upfront investment in both hardware and software. Additionally, organizations might need to factor in costs for ongoing maintenance, support, and infrastructure management. On top of the initial purchase or subscription, some providers may charge additional fees for high-volume traffic, advanced features, or integration with other services, further adding to the overall cost.

What Do Event Brokers Integrate With?

Event brokers are software systems that manage the transmission of event data between different applications or services, typically using event-driven architecture. Various types of software can integrate with event brokers, enabling real-time data processing, automation, and communication between systems. For example, message-oriented middleware (MOM) platforms such as Apache Kafka, RabbitMQ, or ActiveMQ are often used to handle event data streams. These platforms provide the infrastructure necessary for sending and receiving messages between producers and consumers of data.

In addition, microservices architectures often integrate with event brokers. Microservices can publish events or consume events from event brokers to decouple services and enable them to respond to events in real time. Another category is serverless applications. These applications, like AWS Lambda or Azure Functions, can be set up to listen to events on an event broker, triggering functions based on incoming event data.

Event brokers also integrate well with cloud platforms. Many cloud service providers like AWS, Google Cloud, and Microsoft Azure offer managed event streaming services like AWS EventBridge or Google Cloud Pub/Sub. These services enable the integration of event-driven applications with a range of services on their respective platforms, enhancing automation and scalability.

Furthermore, business process management (BPM) and workflow automation software can integrate with event brokers to trigger specific business processes or workflows based on certain events. Enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, and other enterprise software solutions often rely on event brokers to ensure synchronization between different modules and real-time data flow.

Analytics platforms and data processing frameworks, such as Apache Flink or Apache Spark, can consume event data from event brokers, enabling real-time data analytics, monitoring, and decision-making. These systems benefit from the high throughput and low-latency features that event brokers provide, making them essential for environments requiring immediate insights from continuous data streams.

Recent Trends Related to Event Brokers

• Increasing Adoption of Microservices: As organizations shift towards microservices architectures, the need for event brokers grows. Event brokers serve as intermediaries for communication between microservices, allowing them to decouple and scale independently. This trend is pushing the adoption of event-driven designs across industries.
• Rise of Real-Time Data Streaming: Real-time data processing is becoming essential for many industries such as finance, ecommerce, and healthcare. Event brokers are key in enabling real-time data streaming, handling high volumes of data and events, and ensuring that updates or changes are immediately reflected across all systems.
• Cloud-Native Event Brokers: The adoption of cloud-native technologies is pushing the rise of cloud-based event brokers. Solutions like Amazon Kinesis, Azure Event Hubs, and Google Cloud Pub/Sub are gaining popularity because they scale automatically, offer high availability, and reduce the operational burden on organizations.
• Focus on Scalability and Performance: With the growing volume of events in modern systems, event brokers need to handle millions or even billions of events per second. High throughput, low latency, and fault tolerance are becoming more critical, driving the development of more scalable and performant event broker solutions.
• Event-Driven Architecture as a Standard: Event-driven architecture (EDA) is being increasingly adopted by organizations for its flexibility, agility, and decoupled nature. Event brokers play a central role in the implementation of EDA, providing the messaging backbone for events to flow seamlessly across services and systems.
• Integration with Serverless Architectures: Event brokers are becoming essential in serverless environments where functions are triggered by events. By providing reliable, asynchronous communication, event brokers enable serverless architectures to efficiently respond to real-time events without requiring dedicated infrastructure.
• Support for Multiple Protocols: As event brokers evolve, they are expanding their support for multiple messaging protocols such as MQTT, AMQP, and Kafka. This flexibility allows event brokers to integrate with a wide range of applications and devices, especially in IoT ecosystems.
• Event Sourcing and CQRS: Event brokers are playing an important role in event sourcing and Command Query Responsibility Segregation (CQRS) patterns. These architectures rely on event streams to store the state of an application and separate read/write workloads, requiring event brokers to reliably manage the flow of commands and events.
• Security and Compliance: As organizations handle more sensitive data through event-driven systems, security becomes increasingly important. Event brokers are evolving to include enhanced encryption, authentication, and access control mechanisms to meet the security needs of modern enterprise environments.
• Decentralization and Edge Computing: With the rise of edge computing, event brokers are becoming decentralized. Edge devices now need to send events and process data locally before sending it to centralized systems. Event brokers are evolving to work in distributed, edge-based architectures that allow for processing closer to the source of events.
• Integration with Artificial Intelligence and Machine Learning: Event brokers are being integrated with AI and ML technologies. Events can trigger machine learning models to analyze data in real-time, leading to more intelligent systems that can make decisions based on incoming data. Event brokers provide the platform to handle large event volumes needed for AI/ML processing.
• Evolving Standards and Open Source Solutions: Open source event brokers such as Apache Kafka, NATS, and Apache Pulsar are continuing to gain popularity. Their flexible, distributed nature and the community-driven development model are pushing innovation in the event-broker landscape. Additionally, the emergence of open standards for event-driven architectures is providing a more interoperable environment.
• Managed Event Broker Services: The rise of managed event broker services is another significant trend. With services like AWS Managed Streaming for Apache Kafka (MSK), organizations can offload the operational complexity of managing event brokers, ensuring high availability and scalability without the need for dedicated infrastructure.
• Hybrid Event-Driven Architectures: Organizations are increasingly adopting hybrid cloud models where on-premises systems and cloud-based services work together. Event brokers play a key role in enabling seamless communication across these environments, allowing real-time event flow between on-prem and cloud systems.
• Event Mesh and Distributed Event Brokers: The concept of an event mesh is gaining momentum. It connects multiple event brokers across different environments, such as on-premises, cloud, and edge, enabling seamless communication across diverse systems. Distributed event brokers help in creating this mesh by providing a unified, cross-platform event streaming architecture.

How To Select the Best Event Broker

Selecting the right event broker for your system involves considering several key factors based on your requirements. First, you need to think about the scale and performance demands of your application. If you're building a system that requires real-time, high-throughput event processing, then you might need an event broker that can handle a high volume of messages with low latency.

Another important consideration is the level of fault tolerance and reliability your application demands. Some event brokers offer features like message persistence, replication, and automatic failover to ensure that data is not lost during failures. You also need to decide whether the event broker needs to support complex event processing, where you can analyze patterns across multiple events, or if simpler event routing is sufficient.

The compatibility and integration of the event broker with your existing technology stack are also crucial. Ensure that the event broker can easily integrate with the systems and programming languages you're using. You might also need to consider whether the broker supports protocols like HTTP, WebSockets, or Kafka, depending on your needs.

In addition, scalability is essential. Over time, your system may grow in terms of both the number of events and the complexity of processing. The event broker should be able to scale horizontally or vertically to accommodate this growth. Moreover, evaluate the broker’s ecosystem and community support. A well-supported event broker with an active user base can be beneficial, especially when troubleshooting issues or seeking guidance.

Lastly, pricing models are worth considering. Some event brokers operate on a subscription basis, while others might charge based on the volume of events or message throughput. Choose a solution that fits your budget while also meeting the required functionality and performance standards for your system. By weighing these factors, you can select the event broker that aligns best with your technical and business requirements.

Make use of the comparison tools above to organize and sort all of the event brokers products available.