When to use RabbitMQ over Kafka

Question

I ve been asked to evaluate RabbitMQ instead of Kafka but found it hard to find a situation where a message queue is more suitable than Kafka  Does anyone know use cases where a message queue fits better in terms of  throughput  durability  latency  or ease-of-use

User · Answer

I ll provide an objective answer based on my experience with both  I ll also skip the theory behind them  assuming you already know it and or other answers has already provided enough    RabbitMQ  I d pick this one if my requirements are simple enough to deal with system communication through channels queues  retention and streaming is not a requirement  For e g  When the manufacture system built the asset it does notify the agreement system to configure the contracts and so on   Kafka  Event sourcing requirement mainly  when you may need to deal with streams  sometimes infinite   huge amount of data at once properly balanced  replay offsets in order to ensure a given state and so on  Keep in mind that this architecture brings more complexity as well  since it does include concepts such as topics partitions brokers tombstone messages  etc  as a first class importance

User · Answer

The short answer is  message acknowledgements    RabbitMQ can be configured to require message acknowledgements  If a receiver fails the message goes back on the queue and another receiver can try again  While you can accomplish this in Kafka with your own code  it works with RabbitMQ out of the box   In my experience  if you have an application that has requirements to query a stream of information  Kafka and KSql are your best bet  If you want a queueing system you are better off with RabbitMQ

User · Answer

Scaling both is hard in a distributed fault tolerant way but I d make a case that it s much harder at massive scale with RabbitMQ  It s not trivial to understand Shovel  Federation  Mirrored Msg Queues  ACK  Mem issues  Fault tollerance etc  Not to say you won t also have specific issues with Zookeeper etc on Kafka but there are less moving parts to manage  That said  you get a Polyglot exchange with RMQ which you don t with Kafka  If you want streaming  use Kafka  If you want simple IoT or similar high volume packet delivery  use Kafka  It s about smart consumers  If you want msg flexibility and higher reliability with higher costs and possibly some complexity  use RMQ

User · Answer

I realize that this is an old question  but one scenario where RabbitMQ might be a better choice is when dealing with data redaction   With RabbitMQ  by default once the message has been consumed  it s deleted  With Kafka  by default  messages are kept for a week  It s common to set this to a much longer time  or even to never delete them   While both products can be configured to retain  or not retain  messages  if CCPA or GDPR compliance is a concern  I d go with RabbitMQ

User · Answer

One critical difference that you guys forgot is RabbitMQ is push based messaging system whereas Kafka is pull based messaging system  This is important in the scenario where messaging system has to satisfy disparate types of consumers with different processing capabilities  With Pull based system the consumer can consume based on their capability where push systems will push the messages irrespective of the state of consumer thereby putting consumer at high risk

User · Answer

I know it s a bit late and maybe you already  indirectly  said it  but again  Kafka is not a queue at all  it s a log  as someone said above  poll based    To make it simple  the most obvious use case when you should prefer RabbitMQ  or any queue techno  over Kafka is the following one    You have multiple consumers consuming from a queue and whenever there is a new message in the queue and an available consumer  you want this message to be processed  If you look closely at how Kafka works  you ll notice it does not know how to do that  because of partition scaling  you ll have a consumer dedicated to a partition and you ll get into starvation issue  Issue that is easily avoided by using simple queue techno  You can think of using a thread that will dispatch the different messages from same partition  but again  Kafka does not have any selective acknowledgment mechanisms   The most you could do is doing as those guys and try to transform Kafka as a queue   https   github com softwaremill kmq  Yannick

User · Answer

RabbitMQ is a traditional general purpose message broker  It enables web servers to respond to requests quickly and deliver messages to multiple services  Publishers are able to publish messages and make them available to queues  so that consumers can retrieve them  The communication can be either asynchronous or synchronous      On the other hand  Apache Kafka is not just a message broker  It was initially designed and implemented by LinkedIn in order to serve as a message queue  Since 2011  Kafka has been open sourced and quickly evolved into a distributed streaming platform  which is used for the implementation of real-time data pipelines and streaming applications      It is horizontally scalable  fault-tolerant  wicked fast  and runs in   production in thousands of companies    Modern organisations have various data pipelines that facilitate the communication between systems or services  Things get a bit more complicated when a reasonable number of services needs to communicate with each other at real time   The architecture becomes complex since various integrations are required in order to enable the inter-communication of these services  More precisely  for an architecture that encompasses m source and n target services  n x m distinct integrations need to be written  Also  every integration comes with a different specification  meaning that one might require a different protocol  HTTP  TCP  JDBC  etc   or a different data representation  Binary  Apache Avro  JSON  etc    making things even more challenging  Furthermore  source services might address increased load from connections that could potentially impact latency   Apache Kafka leads to more simple and manageable architectures  by decoupling data pipelines  Kafka acts as a high-throughput distributed system where source services push streams of data  making them available for target services to pull them at real-time   Also  a lot of open-source and enterprise-level User Interfaces for managing Kafka Clusters are available now  For more details refer to my articles Overview of UI monitoring tools for Apache Kafka clusters and Why Apache Kafka      The decision of whether to go for RabbitMQ or Kafka is dependent to the requirements of your project  In general  if you want a simple traditional pub-sub message broker then go for RabbitMQ  If you want to build an event-driven architecture on top of which your organisation will be acting on events at real-time  then go for Apache Kafka as it provides more functionality for this architectural type  for example Kafka Streams or ksqlDB

User · Answer

5 Major differences between Kafka and RabbitMQ  customer who are using them    Which messaging system to choose or should we change our existing messaging system    There is no one answer to above question  One possible approach to review when you have to decide which messaging system or should you change existing system is to    Evaluate scope and cost

User · Answer

I hear this question every week    While RabbitMQ  like IBM MQ or JMS or other messaging solutions in general  is used for traditional messaging  Apache Kafka is used as streaming platform  messaging   distributed storage   processing of data   Both are built for different use cases    You can use Kafka for  traditional messaging   but not use MQ for Kafka-specific scenarios    The article    Apache Kafka vs  Enterprise Service Bus  ESB    Friends  Enemies  or Frenemies   https   www confluent io blog apache-kafka-vs-enterprise-service-bus-esb-friends-enemies-or-frenemies      discusses why Kafka is not competitive but complementary to integration and messaging solutions  including RabbitMQ  and how to integrate both

User · Answer

Apache Kafka is a popular choice for powering data pipelines  Apache kafka added kafka stream to support popular etl use cases  KSQL makes it simple to transform data within the pipeline  readying messages to cleanly land in another system  KSQL is the streaming SQL engine for Apache Kafka  It provides an easy-to-use yet powerful interactive SQL interface for stream processing on Kafka  without the need to write code in a programming language such as Java or Python  KSQL is scalable  elastic  fault-tolerant  and real-time  It supports a wide range of streaming operations  including data filtering  transformations  aggregations  joins  windowing  and sessionization   https   docs confluent io current ksql docs index html  Rabbitmq is not a popular choice for etl systems rather for those systems where it requires simple messaging systems with less throughput

User · Answer

The only benefit that I can think of is Transactional feature  rest all can be done by using Kafka

User · Answer

Use RabbitMQ when    You don   t have to handle with Bigdata and you prefer a convenient in-built UI for monitoring  No need of automatically replicable queues No multi subscribers for the messages- Since unlike Kafka which is a log  RabbitMQ is a queue and messages are removed once consumed and acknowledgment arrived If you have the requirements to use Wildcards and regex for messages If defining message priority is important   In Short  RabbitMQ is good for simple use cases  with low traffic of data  with the benefit of priority queue and flexible routing options  For massive data and high throughput use Kafka

User · Answer

Technically  Kafka offers a huge superset of features when compared to the set of features offered by Rabbit MQ   If the question is Is Rabbit MQ technically better than Kafka  then the answer is No   However  if the question is Is Rabbit MQ better than Kafka from a business perspective  then  the answer is Probably  Yes   in some business scenarios  Rabbit MQ can be better than Kafka  from a business perspective  for the following reasons   Maintenance of legacy applications that depend on Rabbit MQ  Staff training cost and steep learning curve required for implementing Kafka  Infrastructure cost for Kafka is higher than that for Rabbit MQ   Troubleshooting problems in Kafka implementation is difficult when compared to that in Rabbit MQ implementation   A Rabbit MQ Developer can easily maintain and support applications that use  Rabbit MQ   The same is not true with Kafka  Experience with just Kafka development is not sufficient to maintain and support applications that use Kafka  The support personnel require other skills like zoo-keeper  networking  disk storage too

User · Answer

RabbitMQ is a solid  general-purpose message broker that supports several protocols such as AMQP  MQTT  STOMP  etc  It can handle high throughput  A common use case for RabbitMQ is to handle background jobs or long-running task  such as file scanning  image scaling or PDF conversion  RabbitMQ is also used between microservices  where it serves as a means of communicating between applications  avoiding bottlenecks passing messages  Kafka is a message bus optimized for high-throughput ingestion data streams and replay  Use Kafka when you have the need to move a large amount of data  process data in real-time or analyze data over a time period  In other words  where data need to be collected  stored  and handled  An example is when you want to track user activity on a webshop and generate suggested items to buy  Another example is data analysis for tracking  ingestion  logging or security  Kafka can be seen as a durable message broker where applications can process and re-process streamed data on disk  Kafka has a very simple routing approach  RabbitMQ has better options if you need to route your messages in complex ways to your consumers  Use Kafka if you need to support batch consumers that could be offline or consumers that want messages at low latency    In order to understand how to read data from Kafka  we first need to understand its consumers and consumer groups  Partitions allow you to parallelize a topic by splitting the data across multiple nodes  Each record in a partition is assigned and identified by its unique offset  This offset points to the record in a partition  In the latest version of Kafka  Kafka maintains a numerical offset for each record in a partition  A consumer in Kafka can either automatically commit offsets periodically  or it can choose to control this committed position manually  RabbitMQ will keep all states about consumed acknowledged unacknowledged messages  I find Kafka more complex to understand than the case of RabbitMQ  where the message is simply removed from the queue once it s acked  RabbitMQ s queues are fastest when they re empty  while Kafka retains large amounts of data with very little overhead - Kafka is designed for holding and distributing large volumes of messages   If you plan to have very long queues in RabbitMQ you could have a look at lazy queues   Kafka is built from the ground up with horizontal scaling  scale by adding more machines  in mind  while RabbitMQ is mostly designed for vertical scaling  scale by adding more power   RabbitMQ has a built-in user-friendly interface that lets you monitor and handle your RabbitMQ server from a web browser  Among other things  queues  connections  channels  exchanges  users and user permissions can be handled - created  deleted and listed in the browser and you can monitor message rates and send receive messages manually  Kafka has a number of open-source tools  and also some commercial once  offering the administration and monitoring functionalities  I would say that it s easier gets faster to get a good understanding of RabbitMQ  In general  if you want a simple traditional pub-sub message broker  the obvious choice is RabbitMQ  as it will most probably scale more than you will ever need it to scale  I would have chosen RabbitMQ if my requirements were simple enough to deal with system communication through channels queues  and where retention and streaming is not a requirement  There are two main situations where I would choose RabbitMQ  For long-running tasks  when I need to run reliable background jobs  And for communication and integration within  and between applications  i e as middleman between microservices  where a system simply needs to notify another part of the system to start to work on a task  like ordering handling in a webshop  order placed  update order status  send order  payment  etc    In general  if you want a framework for storing  reading  re-reading   and analyzing streaming data  use Apache Kafka  It   s ideal for systems that are audited or those that need to store messages permanently  These can also be broken down into two main use cases for analyzing data  tracking  ingestion  logging  security etc   or real-time processing  More reading  use cases and some comparison data can be found here  https   www cloudamqp com blog 2019-12-12-when-to-use-rabbitmq-or-apache-kafka html Also recommending the industry paper   quot Kafka versus RabbitMQ  A comparative study of two industry reference publish subscribe implementations quot   http   dl acm org citation cfm id 3093908 I do work at a company providing both Apache Kafka and RabbitMQ as a Service

User · Answer

The most voted answer covers most part but I would like to high light use case point of view  Can kafka do that rabbit mq can do  answer is yes but can rabbit mq do everything that kafka does  the answer is no  The thing that rabbit mq cannot do that makes kafka apart  is distributed message processing  With this now read back the most voted answer and it will make more sense  To elaborate  take a use case where you need to create a messaging system that has super high throughput for example  quot likes quot  in facebook and You have chosen rabbit mq for that  You created an exchange and queue  and a consumer where all publishers  in this case FB users  can publish  likes  messages  Since your throughput is high  you will create multiple threads in consumer to process messages  in parallel but you still bounded by the hardware capacity of the machine where consumer is running  Assuming that one consumer is not sufficient to process all messages - what would you do   Can you add one more consumer to queue - no you cant do that  Can you create a new queue and bind that queue to exchange that publishes  likes  message  answer is no cause you will have messages processed twice   That is the core problem that kafka solves  It lets you create distributed partitions  Queue in rabbit mq  and distributed consumer that talk to each other  That ensures your messages in a topic get processed by consumers distributed in various nodes  Machines   Kafka brokers ensure that messages get load balanced across all partitions of that topic  Consumer group make sure that all consumer talk to each other and message does not get processed twice  But in real life you will not face this problem unless your throughput is seriously high because rabbit mq can also process data very fast even with one consumer

User · Answer

If you have complex routing needs and want a built-in GUI to monitor the broker  then RabbitMQ might be best for your application   Otherwise  if you   re looking for a message broker to handle high throughput and provide access to stream history  Kafka is the likely the better choice

[apache-kafka] When to use RabbitMQ over Kafka?

Examples related to apache-kafka

Examples related to rabbitmq

Examples related to message-queue