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  5. Kafka vs XMPP

Kafka vs XMPP

OverviewDecisionsComparisonAlternatives

Overview

Kafka
Kafka
Stacks24.2K
Followers22.3K
Votes607
GitHub Stars31.2K
Forks14.8K
XMPP
XMPP
Stacks71
Followers138
Votes0

Kafka vs XMPP: What are the differences?

Introduction

Kafka and XMPP are two widely used messaging protocols, but they have some key differences. Let's explore these differences in detail.

  1. Scalability: Kafka is designed to handle high-volume data streams and can scale horizontally across multiple servers. It ensures fault tolerance and can handle millions of messages per second. On the other hand, XMPP is primarily used for person-to-person communication and although it supports some scalability features, it may not be as efficient in handling large-scale data streams.

  2. Message Delivery Guarantees: Kafka provides strong message delivery guarantees, ensuring that messages are persisted and replicated across multiple servers. It provides at-least-once delivery semantics and allows configurable settings for controlling message acknowledgments and replication factors. XMPP, on the other hand, offers different levels of message reliability ranging from non-persistent (offline messages can be lost) to persistent (messages are stored and guaranteed to be delivered). However, the level of reliability depends on the implementation and server configuration.

  3. Message Types: Kafka is primarily focused on data streams and provides a publish-subscribe messaging model. It allows the storage and processing of various types of messages like logs, event data, and real-time data feeds. XMPP, on the other hand, is an extensible protocol for instant messaging and presence information. It supports a wider range of message types like text, files, and presence status, making it more suitable for real-time person-to-person communication.

  4. Protocol Design: Kafka is designed as a distributed streaming platform and provides a simple and efficient protocol for handling large-scale, fault-tolerant messaging systems. It is optimized for performance and supports high throughput with low latency. XMPP, on the other hand, follows an XML-based protocol design that is more extensible and flexible. It allows the addition of new features and extensions, making it adaptable for different use cases.

  5. Open Standards vs Proprietary: Kafka follows an open-source model and is built on open standards, making it vendor-neutral and widely adopted. It has a large community support and offers a wide range of client libraries and integrations. XMPP, on the other hand, is also an open standard protocol but has been developed by the XMPP Standards Foundation. It has a smaller community and is more commonly associated with proprietary instant messaging applications.

  6. Use Cases: Kafka is commonly used for real-time streaming analytics, log aggregation, and data integration scenarios. It serves as a backbone for data pipelines and supports real-time processing of large volumes of data. XMPP, on the other hand, is mainly used for instant messaging and presence information in applications such as chat, group chat, and online presence detection.

In Summary, Kafka and XMPP differ in terms of scalability, message delivery guarantees, message types, protocol design, openness, and use cases. While Kafka is more suited for handling large-scale data streams and distributed messaging systems, XMPP focuses on real-time person-to-person communication and instant messaging applications.

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Advice on Kafka, XMPP

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
XMPP
XMPP

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

It is a set of open technologies for instant messaging, presence, multi-party chat, voice and video calls, collaboration, lightweight middleware, content syndication, and generalized routing of XML data.

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
-
Statistics
GitHub Stars
31.2K
GitHub Stars
-
GitHub Forks
14.8K
GitHub Forks
-
Stacks
24.2K
Stacks
71
Followers
22.3K
Followers
138
Votes
607
Votes
0
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
No community feedback yet
Integrations
No integrations available
Java
Java
Python
Python
JavaScript
JavaScript

What are some alternatives to Kafka, XMPP?

Kubernetes

Kubernetes

Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.

Rancher

Rancher

Rancher is an open source container management platform that includes full distributions of Kubernetes, Apache Mesos and Docker Swarm, and makes it simple to operate container clusters on any cloud or infrastructure platform.

RabbitMQ

RabbitMQ

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

Docker Compose

Docker Compose

With Compose, you define a multi-container application in a single file, then spin your application up in a single command which does everything that needs to be done to get it running.

Docker Swarm

Docker Swarm

Swarm serves the standard Docker API, so any tool which already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts: Dokku, Compose, Krane, Deis, DockerUI, Shipyard, Drone, Jenkins... and, of course, the Docker client itself.

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.

Tutum

Tutum

Tutum lets developers easily manage and run lightweight, portable, self-sufficient containers from any application. AWS-like control, Heroku-like ease. The same container that a developer builds and tests on a laptop can run at scale in Tutum.

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.

Portainer

Portainer

It is a universal container management tool. It works with Kubernetes, Docker, Docker Swarm and Azure ACI. It allows you to manage containers without needing to know platform-specific code.

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