𝗥𝗮𝗯𝗯𝗶𝘁𝗠𝗤 𝘃𝘀. 𝗞𝗮𝗳𝗸𝗮 𝘃𝘀. 𝗔𝗰𝘁𝗶𝘃𝗲𝗠𝗤: 𝟳 𝐊𝐞

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• 𝗥𝗮𝗯𝗯𝗶𝘁𝗠𝗤 𝘃𝘀. 𝗞𝗮𝗳𝗸𝗮 𝘃𝘀. 𝗔𝗰𝘁𝗶𝘃𝗲𝗠𝗤: 𝟳 𝐊𝐞𝐲 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 🔹𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Kafka is designed for high throughput and horizontal scalability, making it well-suited for handling large volumes of data. RabbitMQ and ActiveMQ both offer high performance, but Kafka generally outperforms them in terms of throughput, particularly in scenarios with high data volume. 🔹𝗠𝗲𝘀𝘀𝗮𝗴𝗲 𝗣𝗿𝗶𝗼𝗿𝗶𝘁𝘆: RabbitMQ and ActiveMQ support message prioritization, allowing messages with higher priority to be processed before those with lower priority. Kafka does not have built-in message priority support. 🔹𝗠𝗲𝘀𝘀𝗮𝗴𝗲 𝗢𝗿𝗱𝗲𝗿𝗶𝗻𝗴: RabbitMQ and ActiveMQ guarantee message ordering within a single queue or topic, respectively. Kafka ensures message ordering within a partition but not across partitions within a topic. 🔹𝗠𝗲𝘀𝘀𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹: RabbitMQ uses a queue-based message model following the Advanced Message Queuing Protocol (AMQP), while Kafka utilizes a distributed log-based model. ActiveMQ is built on the Java Message Service (JMS) standard and also uses a queue-based message model. 🔹𝗗𝘂𝗿𝗮𝗯𝗶𝗹𝗶𝘁𝘆: All three message brokers support durable messaging, ensuring that messages are not lost in case of failures. However, the mechanisms for achieving durability differ among the three, with RabbitMQ and ActiveMQ offering configurable durability options and Kafka providing built-in durability through log replication. 🔹𝗥𝗲𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻: RabbitMQ supports replication through Mirrored Queues, while Kafka features built-in partition replication. ActiveMQ uses a Primary-Replica replication mechanism. 🔹𝗦𝘁𝗿𝗲𝗮𝗺 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴: Kafka provides native stream processing capabilities through Kafka Streams, similarly RabbitMQ offers stream processing too, while ActiveMQ relies on third-party libraries for stream processing. Ref: ✨ RabbitMQ vs. Kafka vs. ActiveMQ: A Battle of Messaging Brokers: https://lnkd.in/g4N7UCPE

• Additionally to what Akhil Nallapaneni said above, if your app is dealing with high volume of messages Kafka is the best for sure, but also, if your app doesn't deal with that high volume, RabbitMQ for example offers more options of delivering the messages, Called exchange types which might be very handy depending on your needs: RabbitMQ Exchange Types There are four basic RabbitMQ exchange types in RabbitMQ, each of which uses different parameters and bindings to route messages in various ways, These are: Direct Exchange Topic Exchange Fanout Exchange Headers Exchange Additionally, there are two more RabbitMQ exchange types: Default Exchange Dead Letter Exchange https://hevodata.com/learn/rabbitmq-exchange-type/#types

• Kafka is beterr than other message queues because 1)Kafka offers much higher performance than any other messaging queue which helps us to deal with high volume of data 2)Kafka replicates the data and is able to support multiple consumers 3)Kafka automatically balances consumers in the event of failure 4)Kafka is faster than other queues, because messages in apache Kafka are not erased once the receiving system has read them, it is easier to log events 5) the way of storage in Kafka is log structured, which mean the new data is append to the end of log If your system deals with higher volumes of data then go with Kafka. Any priority of message are required then go with other ones

• Kafka works on Pull mechanism.. Where as RabbitMQ and ActiveMQ works on push mechanism

• Along with this Kafka uses WAL, and simplfied Sequential IO operations..

• Here are two very good links to understand streams and how there is a difference between systems that support streams and systems that are pure stream based. https://www.oreilly.com/radar/the-world-beyond-batch-streaming-101/ https://www.oreilly.com/radar/the-world-beyond-batch-streaming-102/