RabbitMQ is the most widely used, general-purpose, and open-source message broker. It was released in the year 2007 and was a primary component in messaging systems. Currently, it is used for streaming use cases. RabbitMQ was able to handle the background tasks or act as a message broker between microservices. It helped the web applications in reducing the loads. Also, it reduced the delivery time of the servers for those tasks or resources which were time-consuming.
Apache Kafka is also an open-source distributed pub/sub message system. It was released in the year 2011 which works as middle storage between two applications. The producer writes and stores the message in the Kafka cluster. On the other hand, the consumer consumes messages from the cluster. It also reduces the slow delivery of heavy messages.
||Kafka consumers get distributed through topic partitions. Each consumer consumes messages from a specific partition at a time.
||There are a number of consumers present for each queue instance. These consumers are known as Competitive consumers as they compete with one another for consuming the message. But, the message can be processed just once.
||With the help of zookeeper, it manages the state of the Kafka cluster and supports high availability.
||Through clustering and high available queues provides high-performance data replication. Thus, it also provides high availability.
||It can process millions of messages in a second with less number of the hardware.
||It can also process millions of messages within a second, but it needs more number of the hardware.
||There are replicated brokers available in Kafka, which works when the master broker is down.
||Here, queues are not automatically replicated. The configuration is mandatory.
||Multiple consumer types can subscribe to many messages to Kafka.
||Although messages are routed to various queues, only one consumer from a queue can process the message.
||Apache Kafka supports primitives such as int8, int16, etc. and binary messages.
||This supports any standard queue protocols such as STOMP, AMQP, HTTP, etc.
||Message ordering is present inside the partition only. It guarantees that either all fail or pass together.
||It maintains the order for flows via a single AMQP channel. In addition, it also reorders the retransmitted packets inside its queue logic that will prevent the consumer from resequencing the buffers.
||It contains a log file that prevents all messages anytime.
||Since it is a queue, messages once consumed are removed, and the acknowledgment is received.
||Highly scalable pub/sub distributed messaging system. It has brokers, topics, partitions, and topics within the Kafka cluster.
||A general-purpose pub/sub message broker. Its architecture varies from Kafka as it consists of queues.
||It is mainly used for streaming the data.
||The web servers mainly use it for immediate response to the requests.
||It supports those transactions that exhibit a ?read-process-write? pattern performed to/from Kafka topics.
||It does not guarantee atomicity even when the transaction indulges only a single queue.
||Apache Kafka is written in Scala with JVM.
||RabbitMQ is written in Erlang.
||It supports complex routing scenarios.
||It does not support complex routing scenarios.
||With high growth, it led to a good experience. But, it only supports Java clients.
||RabbitMQ carries mature client libraries that support Java, PHP, Python, Ruby, and many more.