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  5. Kafka vs NATS vs ZeroMQ

Kafka vs NATS vs ZeroMQ

OverviewDecisionsComparisonAlternatives

Overview

Kafka
Kafka
Stacks24.2K
Followers22.3K
Votes607
GitHub Stars31.2K
Forks14.8K
ZeroMQ
ZeroMQ
Stacks258
Followers586
Votes71
GitHub Stars10.6K
Forks2.5K
NATS
NATS
Stacks394
Followers498
Votes60

Kafka vs NATS vs ZeroMQ: What are the differences?

Introduction

When considering messaging systems for your applications, it's essential to understand the key differences between popular tools like Kafka, NATS, and ZeroMQ. Each of these tools has its unique characteristics that can significantly impact the performance and scalability of your system.

  1. Scalability: Kafka is designed for storing and processing large volumes of data, making it highly scalable for handling high-throughput use cases. NATS, on the other hand, is more lightweight and focused on simplicity and speed, making it a good choice for low-latency messaging. ZeroMQ falls in between the two, offering high performance and low latency but may require more configuration for scaling to large distributed systems.

  2. Persistence: Kafka stores messages in a distributed commit log that provides fault tolerance and durability, making it well-suited for use cases where data persistence is crucial. NATS, being more lightweight, does not provide built-in persistence but can be integrated with external databases for storage. ZeroMQ does not have built-in persistence and focuses more on real-time messaging with minimal overhead.

  3. Protocols: Kafka uses the TCP protocol for communication between clients and servers, providing reliable and ordered message delivery. NATS, on the other hand, uses a custom proprietary protocol optimized for low-latency messaging. ZeroMQ supports multiple transport protocols, including TCP, inproc, IPC, and PGM, offering flexibility in communication options.

  4. Pub-Sub vs. Point-to-Point: Kafka supports both publish-subscribe and point-to-point messaging patterns, making it versatile for different use cases. NATS is primarily designed for publish-subscribe messaging, emphasizing simplicity and efficiency. ZeroMQ is a socket library that allows you to build custom messaging patterns, including pub-sub, push-pull, and request-reply.

  5. Community and Ecosystem: Kafka has a vibrant open-source community and a wide range of plugins and integrations, making it a popular choice for many organizations. NATS also has an active community and ecosystem but is more focused on its core messaging capabilities without as many additional features. ZeroMQ has a smaller but dedicated community that values its lightweight and flexible design.

  6. Complexity: Kafka is more complex to set up and manage due to its distributed nature and reliance on Zookeeper for coordination. NATS is lightweight and easy to get started with but may lack some advanced features required for complex use cases. ZeroMQ requires more manual configuration and development effort but offers fine-grained control over messaging patterns and performance.

In Summary, choosing the right messaging system depends on your specific requirements for scalability, persistence, protocols, messaging patterns, community support, and complexity in setup and maintenance. Each tool has its strengths and weaknesses, so it's essential to evaluate them based on your application's needs.

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Advice on Kafka, ZeroMQ, NATS

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
ZeroMQ
ZeroMQ
NATS
NATS

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

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.

Unlike traditional enterprise messaging systems, NATS has an always-on dial tone that does whatever it takes to remain available. This forms a great base for building modern, reliable, and scalable cloud and distributed systems.

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
Connect your code in any language, on any platform.;Carries messages across inproc, IPC, TCP, TPIC, multicast.;Smart patterns like pub-sub, push-pull, and router-dealer.;High-speed asynchronous I/O engines, in a tiny library.;Backed by a large and active open source community.;Supports every modern language and platform.;Build any architecture: centralized, distributed, small, or large.;Free software with full commercial support.
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Statistics
GitHub Stars
31.2K
GitHub Stars
10.6K
GitHub Stars
-
GitHub Forks
14.8K
GitHub Forks
2.5K
GitHub Forks
-
Stacks
24.2K
Stacks
258
Stacks
394
Followers
22.3K
Followers
586
Followers
498
Votes
607
Votes
71
Votes
60
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
  • 23
    Fast
  • 20
    Lightweight
  • 11
    Transport agnostic
  • 7
    No broker required
  • 4
    Low latency
Cons
  • 5
    No message durability
  • 3
    Not a very reliable system - message delivery wise
  • 1
    M x N problem with M producers and N consumers
Pros
  • 22
    Fastest pub-sub system out there
  • 16
    Rock solid
  • 12
    Easy to grasp
  • 4
    Light-weight
  • 4
    Easy, Fast, Secure
Cons
  • 2
    Persistence with Jetstream supported
  • 1
    No Persistence
  • 1
    No Order

What are some alternatives to Kafka, ZeroMQ, NATS?

Firebase

Firebase

Firebase is a cloud service designed to power real-time, collaborative applications. Simply add the Firebase library to your application to gain access to a shared data structure; any changes you make to that data are automatically synchronized with the Firebase cloud and with other clients within milliseconds.

Socket.IO

Socket.IO

It enables real-time bidirectional event-based communication. It works on every platform, browser or device, focusing equally on reliability and speed.

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.

PubNub

PubNub

PubNub makes it easy for you to add real-time capabilities to your apps, without worrying about the infrastructure. Build apps that allow your users to engage in real-time across mobile, browser, desktop and server.

Pusher

Pusher

Pusher is the category leader in delightful APIs for app developers building communication and collaboration features.

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.

SignalR

SignalR

SignalR allows bi-directional communication between server and client. Servers can now push content to connected clients instantly as it becomes available. SignalR supports Web Sockets, and falls back to other compatible techniques for older browsers. SignalR includes APIs for connection management (for instance, connect and disconnect events), grouping connections, and authorization.

Ably

Ably

Ably offers WebSockets, stream resume, history, presence, and managed third-party integrations to make it simple to build, extend, and deliver digital realtime experiences at scale.

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