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  5. Gearman vs Kafka vs apache nifi

Gearman vs Kafka vs apache nifi

OverviewDecisionsComparisonAlternatives

Overview

Kafka
Kafka
Stacks24.2K
Followers22.3K
Votes607
GitHub Stars31.2K
Forks14.8K
Gearman
Gearman
Stacks77
Followers144
Votes45

Gearman vs Kafka: What are the differences?

Developers describe Gearman as "A generic application framework to farm out work to other machines or processes". 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. On the other hand, Kafka is detailed 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.

Gearman and Kafka can be categorized as "Message Queue" tools.

Some of the features offered by Gearman are:

  • Open Source It’s free! (in both meanings of the word) Gearman has an active open source community that is easy to get involved with if you need help or want to contribute. Worried about licensing? Gearman is BSD
  • Multi-language - There are interfaces for a number of languages, and this list is growing. You also have the option to write heterogeneous applications with clients submitting work in one language and workers performing that work in another
  • Flexible - You are not tied to any specific design pattern. You can quickly put together distributed applications using any model you choose, one of those options being Map/Reduce

On the other hand, Kafka provides the following key features:

  • Written at LinkedIn in Scala
  • Used by LinkedIn to offload processing of all page and other views
  • Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled)

"Free" is the top reason why over 10 developers like Gearman, while over 95 developers mention "High-throughput" as the leading cause for choosing Kafka.

Kafka is an open source tool with 13.1K GitHub stars and 6.99K GitHub forks. Here's a link to Kafka's open source repository on GitHub.

According to the StackShare community, Kafka has a broader approval, being mentioned in 691 company stacks & 2398 developers stacks; compared to Gearman, which is listed in 27 company stacks and 33 developer stacks.

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Advice on Kafka, Gearman

viradiya
viradiya

Apr 12, 2020

Needs adviceonAngularJSAngularJSASP.NET CoreASP.NET CoreMSSQLMSSQL

We are going to develop a microservices-based application. It consists of AngularJS, ASP.NET Core, and MSSQL.

We have 3 types of microservices. Emailservice, Filemanagementservice, Filevalidationservice

I am a beginner in microservices. But I have read about RabbitMQ, but come to know that there are Redis and Kafka also in the market. So, I want to know which is best.

933k views933k
Comments
Ishfaq
Ishfaq

Feb 28, 2020

Needs advice

Our backend application is sending some external messages to a third party application at the end of each backend (CRUD) API call (from UI) and these external messages take too much extra time (message building, processing, then sent to the third party and log success/failure), UI application has no concern to these extra third party messages.

So currently we are sending these third party messages by creating a new child thread at end of each REST API call so UI application doesn't wait for these extra third party API calls.

I want to integrate Apache Kafka for these extra third party API calls, so I can also retry on failover third party API calls in a queue(currently third party messages are sending from multiple threads at the same time which uses too much processing and resources) and logging, etc.

Question 1: Is this a use case of a message broker?

Question 2: If it is then Kafka vs RabitMQ which is the better?

804k views804k
Comments
Roman
Roman

Senior Back-End Developer, Software Architect

Feb 12, 2019

ReviewonKafkaKafka

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)
10.9k views10.9k
Comments

Detailed Comparison

Kafka
Kafka
Gearman
Gearman

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

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.

Written at LinkedIn in Scala;Used by LinkedIn to offload processing of all page and other views;Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled);Supports both on-line as off-line processing
Open Source It’s free! (in both meanings of the word) Gearman has an active open source community that is easy to get involved with if you need help or want to contribute. Worried about licensing? Gearman is BSD;Multi-language - There are interfaces for a number of languages, and this list is growing. You also have the option to write heterogeneous applications with clients submitting work in one language and workers performing that work in another;Flexible - You are not tied to any specific design pattern. You can quickly put together distributed applications using any model you choose, one of those options being Map/Reduce;Fast - Gearman has a simple protocol and interface with an optimized, and threaded, server written in C/C++ to minimize your application overhead;Embeddable - Since Gearman is fast and lightweight, it is great for applications of all sizes. It is also easy to introduce into existing applications with minimal overhead;No single point of failure - Gearman can not only help scale systems, but can do it in a fault tolerant way;No limits on message size - Gearman supports single messages up to 4gig in size. Need to do something bigger? No problem Gearman can chunk messages;Worried about scaling? - Don’t worry about it with Gearman. Craig’s List, Tumblr, Yelp, Etsy,… discover what others have known for years.
Statistics
GitHub Stars
31.2K
GitHub Stars
-
GitHub Forks
14.8K
GitHub Forks
-
Stacks
24.2K
Stacks
77
Followers
22.3K
Followers
144
Votes
607
Votes
45
Pros & Cons
Pros
  • 126
    High-throughput
  • 119
    Distributed
  • 92
    Scalable
  • 86
    High-Performance
  • 66
    Durable
Cons
  • 32
    Non-Java clients are second-class citizens
  • 29
    Needs Zookeeper
  • 9
    Operational difficulties
  • 5
    Terrible Packaging
Pros
  • 11
    Ease of use and very simple APIs
  • 11
    Free
  • 6
    Polyglot
  • 5
    No single point of failure
  • 3
    Scalable

What are some alternatives to Kafka, Gearman?

RabbitMQ

RabbitMQ

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Celery

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.

Amazon SQS

Amazon SQS

Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.

NSQ

NSQ

NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

ActiveMQ

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.

ZeroMQ

ZeroMQ

The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.

Apache NiFi

Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

Memphis

Memphis

Highly scalable and effortless data streaming platform. Made to enable developers and data teams to collaborate and build real-time and streaming apps fast.

IronMQ

IronMQ

An easy-to-use highly available message queuing service. Built for distributed cloud applications with critical messaging needs. Provides on-demand message queuing with advanced features and cloud-optimized performance.

Apache Pulsar

Apache Pulsar

Apache Pulsar is a distributed messaging solution developed and released to open source at Yahoo. Pulsar supports both pub-sub messaging and queuing in a platform designed for performance, scalability, and ease of development and operation.

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