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Kafka vs Sidekiq: What are the differences?

Developers describe Kafka as "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. On the other hand, Sidekiq is detailed as "Simple, efficient background processing for Ruby". Sidekiq uses threads to handle many jobs at the same time in the same process. It does not require Rails but will integrate tightly with Rails 3/4 to make background processing dead simple.

Kafka and Sidekiq are primarily classified as "Message Queue" and "Background Processing" tools respectively.

"High-throughput", "Distributed" and "Scalable" are the key factors why developers consider Kafka; whereas "Simple", "Efficient background processing" and "Scalability" are the primary reasons why Sidekiq is favored.

Kafka and Sidekiq are both open source tools. It seems that Kafka with 12.7K GitHub stars and 6.81K forks on GitHub has more adoption than Sidekiq with 9.68K GitHub stars and 1.66K GitHub forks.

According to the StackShare community, Kafka has a broader approval, being mentioned in 509 company stacks & 470 developers stacks; compared to Sidekiq, which is listed in 348 company stacks and 77 developer stacks.

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.

What is Sidekiq?

Sidekiq uses threads to handle many jobs at the same time in the same process. It does not require Rails but will integrate tightly with Rails 3/4 to make background processing dead simple.
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    What are some alternatives to Kafka and Sidekiq?
    ActiveMQ
    Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.
    RabbitMQ
    RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
    Amazon Kinesis
    Amazon Kinesis can collect and process hundreds of gigabytes of data per second from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data.
    Apache Spark
    Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
    Akka
    Akka is a toolkit and runtime for building highly concurrent, distributed, and resilient message-driven applications on the JVM.
    See all alternatives
    Decisions about Kafka and Sidekiq
    Jerome Dalbert
    Jerome Dalbert
    Senior Backend Engineer at StackShare | 4 upvotes 58.7K views
    atGratify CommerceGratify Commerce
    delayed_job
    delayed_job
    Rails
    Rails
    AWS Elastic Beanstalk
    AWS Elastic Beanstalk
    Sidekiq
    Sidekiq
    Ruby
    Ruby
    Amazon SQS
    Amazon SQS
    #BackgroundProcessing

    delayed_job is a great Rails background job library for new projects, as it only uses what you already have: a relational database. We happily used it during the company鈥檚 first two years.

    But it started to falter as our web and database transactions significantly grew. Our app interacted with users via SMS texts sent inside background jobs. Because the delayed_job daemon ran every couple seconds, this meant that users often waited several long seconds before getting text replies, which was not acceptable. Moreover, job processing was done inside AWS Elastic Beanstalk web instances, which were already under stress and not meant to handle jobs.

    We needed a fast background job system that could process jobs in near real-time and integrate well with AWS. Sidekiq is a fast and popular Ruby background job library, but it does not leverage the Elastic Beanstalk worker architecture, and you have to maintain a Redis instance.

    We ended up choosing active-elastic-job, which seamlessly integrates with worker instances and Amazon SQS. SQS is a fast queue and you don鈥檛 need to worry about infrastructure or scaling, as AWS handles it for you.

    We noticed significant performance gains immediately after making the switch.

    #BackgroundProcessing

    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
    Kafka
    Kafka
    RabbitMQ
    RabbitMQ

    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 129.8K views
    atOSInetOSInet
    Beanstalkd
    Beanstalkd
    RabbitMQ
    RabbitMQ
    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
    Jerome Dalbert
    Jerome Dalbert
    Senior Backend Engineer at StackShare | 3 upvotes 37.8K views
    atStackShareStackShare
    Sidekiq
    Sidekiq
    Ruby
    Ruby
    delayed_job
    delayed_job
    Redis
    Redis

    We use Sidekiq to process millions of Ruby background jobs a day under normal loads. We sometimes process more than that when running one-off backfill tasks.

    With so many jobs, it wouldn't really make sense to use delayed_job, as it would put our main database under unnecessary load, which would make it a bottleneck with most DB queries serving jobs and not end users. I suppose you could create a separate DB just for jobs, but that can be a hassle. Sidekiq uses a separate Redis instance so you don't have this problem. And it is very performant!

    I also like that its free version comes "batteries included" with:

    • A web monitoring UI that provides some nice stats.
    • An API that can come in handy for one-off tasks, like changing the queue of certain already enqueued jobs.

    Sidekiq is a pleasure to use. All our engineers love it!

    See more
    Interest over time
    Reviews of Kafka and Sidekiq
    Review ofSidekiqSidekiq

    Pretty good post. I found your website perfect for my needs bullet force

    How developers use Kafka and Sidekiq
    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 SmartLogic
    SmartLogic uses SidekiqSidekiq

    We turn to Sidekiq when we need to run background jobs in a Rails app, which we do for just about every Rails app we write. We especially like the ops tools that come with Sidekiq, which make it easy to monitor and maintain.

    Avatar of Tim Lucas
    Tim Lucas uses SidekiqSidekiq

    Background processing of Pushover push notifications to admins when sales occur, payments processing via Pin Payments, Campaign Monitor transaction email sending, and Intercom event API posting.

    Avatar of Told
    Told uses SidekiqSidekiq

    Sidekiq is used extensively for a multitude of background jobs, everything from audio/video post-processing to sending push notifications.

    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 Jeff Flynn
    Jeff Flynn uses SidekiqSidekiq

    We offload our background processing tasks (photo sizing, watermarking, etc.) to Sidekiq to keep our app's performance optimal.

    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.

    How much does Kafka cost?
    How much does Sidekiq cost?
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