In an IoT scenario, we might want to have each producer’s identity map to a specific partition constantly. For example, in a multitenant application, we might want to create logical message streams according to every message’s tenant ID. Producers can modify this behavior to create logical streams of messages. By default, it uses a round-robin partitioner to spread messages uniformly across partitions. Kafka appends messages to these partitions as they arrive. Each partition is an ordered, immutable sequence of records, where messages are continually appended. Instead, Kafka stores collections of records in categories called topics.įor each topic, Kafka maintains a partitioned log of messages. Kafka doesn’t implement the notion of a queue. There are also cloud-specific and open-source alternatives to Kafka’s stream processing capabilities, but, again, these are out of the scope of this post. These solutions include Azure Event Hubs and, to some extent, AWS Kinesis Data Streams. The cloud vendors provide alternative solutions for Kafka’s storage layer. Kafka also provides a Streams API to process streams in real time and a Connectors API for easy integration with various data sources however, these are out of the scope of this piece. Unlike RabbitMQ, which is based on queues and exchanges, Kafka’s storage layer is implemented using a partitioned transaction log. Instead, it’s a distributed streaming platform. It can also filter messages for some subscribers based on various routing rules.Īpache Kafka isn’t an implementation of a message broker. A publisher publishes its messages to a message exchange without knowing who the subscribers of these messages are.Įach consumer wishing to subscribe to an exchange creates a queue the message exchange then queues produced messages for consumers to consume. RabbitMQ implements pub/sub via the use of message exchanges. Consumers, in turn, use the same queue to retrieve messages to process them. A developer defines named queues, and then publishers can send messages to that named queue. RabbitMQ supports classic message queuing out of the box. All of these implementations have a lot in common many concepts described in this piece apply to most of them. Other popular implementations of message brokers include ActiveMQ, ZeroMQ, Azure Service Bus, and Amazon Simple Queue Service (SQS). It natively supports both messaging patterns described above. RabbitMQ is an implementation of a message broker - often referred to as a service bus.
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