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Beanstalkd vs Kafka: What are the differences?

What is Beanstalkd? A simple, fast work queue. Beanstalks's interface is generic, but was originally designed for reducing the latency of page views in high-volume web applications by running time-consuming tasks asynchronously.

What is Kafka? Distributed, fault tolerant, high throughput pub-sub messaging system. Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

Beanstalkd belongs to "Background Processing" category of the tech stack, while Kafka can be primarily classified under "Message Queue".

"Fast" is the top reason why over 20 developers like Beanstalkd, while over 95 developers mention "High-throughput" as the leading cause for choosing Kafka.

Beanstalkd and Kafka are both open source tools. Kafka with 12.7K GitHub stars and 6.81K forks on GitHub appears to be more popular than Beanstalkd with 5.12K GitHub stars and 748 GitHub forks.

Uber Technologies, Spotify, and Slack are some of the popular companies that use Kafka, whereas Beanstalkd is used by Douban, Rollbar, and Vigil. Kafka has a broader approval, being mentioned in 509 company stacks & 470 developers stacks; compared to Beanstalkd, which is listed in 27 company stacks and 8 developer stacks.

What is Beanstalkd?

Beanstalks's interface is generic, but was originally designed for reducing the latency of page views in high-volume web applications by running time-consuming tasks asynchronously.

What is Kafka?

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
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      What are some alternatives to Beanstalkd and Kafka?
      RabbitMQ
      RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
      Redis
      Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
      Resque
      Background jobs can be any Ruby class or module that responds to perform. Your existing classes can easily be converted to background jobs or you can create new classes specifically to do work. Or, you can do both.
      Gearman
      Gearman allows you to do work in parallel, to load balance processing, and to call functions between languages. It can be used in a variety of applications, from high-availability web sites to the transport of database replication events.
      Celery
      Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.
      See all alternatives
      Decisions about Beanstalkd and Kafka
      Adam Rabinovitch
      Adam Rabinovitch
      Global Technical Recruiting Lead & Engineering Evangelist at Beamery | 3 upvotes 156.9K views
      atBeameryBeamery
      Kafka
      Kafka
      Redis
      Redis
      Elasticsearch
      Elasticsearch
      MongoDB
      MongoDB
      RabbitMQ
      RabbitMQ
      Go
      Go
      Node.js
      Node.js
      Kubernetes
      Kubernetes
      #Microservices

      Beamery runs a #microservices architecture in the backend on top of Google Cloud with Kubernetes There are a 100+ different microservice split between Node.js and Go . Data flows between the microservices over REST and gRPC and passes through Kafka RabbitMQ as a message bus. Beamery stores data in MongoDB with near-realtime replication to Elasticsearch . In addition, Beamery uses Redis for various memory-optimized tasks.

      See more
      Conor Myhrvold
      Conor Myhrvold
      Tech Brand Mgr, Office of CTO at Uber | 4 upvotes 100.8K views
      atUber TechnologiesUber Technologies
      Kafka Manager
      Kafka Manager
      Kafka
      Kafka
      GitHub
      GitHub
      Apache Spark
      Apache Spark
      Hadoop
      Hadoop

      Why we built Marmaray, an open source generic data ingestion and dispersal framework and library for Apache Hadoop :

      Built and designed by our Hadoop Platform team, Marmaray is a plug-in-based framework built on top of the Hadoop ecosystem. Users can add support to ingest data from any source and disperse to any sink leveraging the use of Apache Spark . The name, Marmaray, comes from a tunnel in Turkey connecting Europe and Asia. Similarly, we envisioned Marmaray within Uber as a pipeline connecting data from any source to any sink depending on customer preference:

      https://eng.uber.com/marmaray-hadoop-ingestion-open-source/

      (Direct GitHub repo: https://github.com/uber/marmaray Kafka Kafka Manager )

      See more
      Roman Bulgakov
      Roman Bulgakov
      Senior Back-End Developer, Software Architect at Chemondis GmbH | 3 upvotes 10.5K views
      Kafka
      Kafka

      I use Kafka because it has almost infinite scaleability in terms of processing events (could be scaled to process hundreds of thousands of events), great monitoring (all sorts of metrics are exposed via JMX).

      Downsides of using Kafka are: - you have to deal with Zookeeper - you have to implement advanced routing yourself (compared to RabbitMQ it has no advanced routing)

      See more
      RabbitMQ
      RabbitMQ
      Kafka
      Kafka

      The question for which Message Queue to use mentioned "availability, distributed, scalability, and monitoring". I don't think that this excludes many options already. I does not sound like you would take advantage of Kafka's strengths (replayability, based on an even sourcing architecture). You could pick one of the AMQP options.

      I would recommend the RabbitMQ message broker, which not only implements the AMQP standard 0.9.1 (it can support 1.x or other protocols as well) but has also several very useful extensions built in. It ticks the boxes you mentioned and on top you will get a very flexible system, that allows you to build the architecture, pick the options and trade-offs that suite your case best.

      For more information about RabbitMQ, please have a look at the linked markdown I assembled. The second half explains many configuration options. It also contains links to managed hosting and to libraries (though it is missing Python's - which should be Puka, I assume).

      See more
      Fr茅d茅ric MARAND
      Fr茅d茅ric MARAND
      Core Developer at OSInet | 2 upvotes 88.7K views
      atOSInetOSInet
      RabbitMQ
      RabbitMQ
      Beanstalkd
      Beanstalkd
      Kafka
      Kafka

      I used Kafka originally because it was mandated as part of the top-level IT requirements at a Fortune 500 client. What I found was that it was orders of magnitude more complex ...and powerful than my daily Beanstalkd , and far more flexible, resilient, and manageable than RabbitMQ.

      So for any case where utmost flexibility and resilience are part of the deal, I would use Kafka again. But due to the complexities involved, for any time where this level of scalability is not required, I would probably just use Beanstalkd for its simplicity.

      I tend to find RabbitMQ to be in an uncomfortable middle place between these two extremities.

      See more
      Interest over time
      Reviews of Beanstalkd and Kafka
      No reviews found
      How developers use Beanstalkd and Kafka
      Avatar of Pinterest
      Pinterest uses KafkaKafka

      http://media.tumblr.com/d319bd2624d20c8a81f77127d3c878d0/tumblr_inline_nanyv6GCKl1s1gqll.png

      Front-end messages are logged to Kafka by our API and application servers. We have batch processing (on the middle-left) and real-time processing (on the middle-right) pipelines to process the experiment data. For batch processing, after daily raw log get to s3, we start our nightly experiment workflow to figure out experiment users groups and experiment metrics. We use our in-house workflow management system Pinball to manage the dependencies of all these MapReduce jobs.

      Avatar of Coolfront Technologies
      Coolfront Technologies uses KafkaKafka

      Building out real-time streaming server to present data insights to Coolfront Mobile customers and internal sales and marketing teams.

      Avatar of ShareThis
      ShareThis uses KafkaKafka

      We are using Kafka as a message queue to process our widget logs.

      Avatar of Christopher Davison
      Christopher Davison uses KafkaKafka

      Used for communications and triggering jobs across ETL systems

      Avatar of theskyinflames
      theskyinflames uses KafkaKafka

      Used as a integration middleware by messaging interchanging.

      Avatar of Snaplytics
      Snaplytics uses BeanstalkdBeanstalkd

      Beanstalkd is used as a job/task queue

      Avatar of Roy Olsen
      Roy Olsen uses BeanstalkdBeanstalkd

      Message and task queue

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