11/2/2023 0 Comments Message queue comparisonThese event flows are the powerful routing capabilities that make RabbitMQ so famous. Developers subscribe event consumers to queues and can route When using RabbitMQ, a popular open source message broker, events can be pushedĭirectly to queues or to exchanges of the This is typically referred to as the smart broker/ dumb consumers dynamic. With traditional message brokers, the event router is intelligent while the event consumers are more reactive than proactive. These traditional message brokers are persistent message frameworks that fuel the flow of events in an application's event-driven architecture. Some examples ofĬommon message queues include RabbitMQ and Redis. Transmit messages between event producers and event routers. This post was written alongside our other event-driven architecture articles, Introduction to Synchronous and Asynchronous Processing and Understanding Event-Driven Architecture and Serverless Opportunities Traditional Message Brokers are Persistent and Highly CentralizedĮarlier versions of event-driven architectures relied on message queues to We'll look at how these event routers work, their respective advantages and drawbacks before considering their better-fit use cases. That is why today we are going to review the differences between traditional message brokers like RabbitMQ and modern event streamers like Apache Kafka. Understanding their capabilities and limitations provides key insights that empower you to confidently decide which one to use and prepare you to navigate its shortcomings. Not all implementations of event routers are the same, nor do any of them offer an all-purpose solution, so deciding which one to use depends on your use case and project's needs. Therefore, ApsaraMQ for Kafka limits the length of the group name.ĪpsaraMQ for Kafka allows you to manage groups in the console or by calling API operations to implement security management features such as resource actions audit and fine-grained permission control.In an event-driven architecture, event routers are the components that connect event consumers to event producers. If the name of a group is excessively long, data transmission of the group in other systems may be limited. The name can contain letters, digits, underscores (_), hyphens (-), and periods (.), and must be 3 to 249 characters in length. The name can contain letters, digits, underscores (_), hyphens (-), and periods (.), and must be 3 to 64 characters in length. After you enable the flexible group creation feature, you cannot use the features such as fine-grained permission control, resource actions audit, and monitoring and alerting of accumulated messages for groups. If you want a group to be automatically created on the broker, see Use the flexible group creation feature. On that premise, ApsaraMQ for Kafka imposes the following limits on user habits to provide more message management and governance features.Īutomatic topic creation on a broker (disabled by default)ĪpsaraMQ for Kafka allows you to manage topics in the console or by calling API operations to implement security management features such as resource actions audit and fine-grained permission control. Therefore, you can seamlessly migrate applications and code that are developed by using open source Apache Kafka to ApsaraMQ for Kafka. However, you cannot view messages by point in time or by offset.ĪpsaraMQ for Kafka is consistent with open source Apache Kafka in terms of client protocols. You can consume messages by running commands in the CLI. You can query messages by point in time or by offset in the console. You can send messages only by running commands in the CLI. Historical data is difficult to access.Īlerts on message accumulation can be triggered for troubleshooting at the earliest opportunity.Ī complete partition status diagram is provided.Ī brief partition status diagram is provided. Manual upgrade, which is prone to errors.Ī complete metrics curve facilitates traffic tracing and troubleshooting. The highly reliable cloud storage of the Professional Edition helps you save large amounts of storage space.įor availability and reliability reasons, data is stored in three replicas. Cluster performance is affected by increased replication traffic. Scaling is completed in seconds without affecting the business. Jitter occurs frequently when the number of partitions exceeds 1,000.ĭeadlocks and breakdowns can be automatically detected and fixed.īugs can be detected and fixed at the earliest opportunity.īugs cannot be fixed until the community releases new versions, which takes a long time. This causes frequent data write failures.ĭata writes are stable even when the number of partitions is over 10,000. Threads are blocked when cold data is being read. Earlier data is deleted when no free disk space is available.īreakdowns occur when no free disk space is available.ĭata writes are normal when cold data is being read.
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