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  5. Apache RocketMQ vs Kafka vs NSQ

Apache RocketMQ vs Kafka vs NSQ

OverviewDecisionsComparisonAlternatives

Overview

Kafka
Kafka
Stacks24.2K
Followers22.3K
Votes607
GitHub Stars31.2K
Forks14.8K
NSQ
NSQ
Stacks142
Followers356
Votes148
Apache RocketMQ
Apache RocketMQ
Stacks48
Followers200
Votes8

Apache RocketMQ vs Kafka vs NSQ: What are the differences?

Introduction

In the modern landscape of data processing, Apache RocketMQ, Kafka, and NSQ are popular distributed messaging systems that play a crucial role in allowing seamless communication between various components of a system. Each platform offers unique features and characteristics that set them apart from one another. Below are the key differences between Apache RocketMQ, Kafka, and NSQ.

  1. Scalability: Apache RocketMQ is designed to be highly scalable, supporting up to one million of topics and providing linear scalability in both producers and consumers. In contrast, Kafka also offers scalability but primarily focuses on horizontal scaling across multiple nodes. NSQ, on the other hand, is known for its simplistic design and ease of use, supporting only a single topic per channel which can limit scalability compared to RocketMQ and Kafka.

  2. Message Delivery Guarantees: In terms of message delivery guarantees, Kafka offers strong durability and fault-tolerance by persisting messages to disk. It provides exactly-once semantics through mechanisms like idempotent producers and transaction support. RocketMQ also provides strong consistency guarantees with its robust message persistence mechanism. NSQ, however, prioritizes speed over durability, favoring at-least-once delivery semantics while sacrificing message durability.

  3. Community and Ecosystem: Kafka has a vibrant and extensive community with a rich ecosystem of tools and libraries, making it a popular choice for many organizations. Apache RocketMQ, backed by the Alibaba Group, also has a growing community and provides compatibility with various programming languages. NSQ, although less widely adopted, has a dedicated user base and community that appreciates its simplicity and performance.

  4. Architecture and Design Philosophy: Kafka follows a distributed commit log architecture where messages are stored in topics and partitioned across multiple brokers for high throughput. RocketMQ adopts a Broker-Cluster architecture with separate components for nameservers, brokers, and console components, providing a more modular approach to messaging. NSQ relies on decentralized architecture with no central brokers, making it a lightweight solution suitable for microservices architectures.

  5. Monitoring and Management: Kafka provides a robust set of tools for monitoring cluster health, offset management, and performance tuning, such as Kafka Manager and Confluent Control Center. RocketMQ offers a web-based console for monitoring and managing clusters, while NSQ provides basic monitoring capabilities like nsqadmin for real-time statistics and administration.

  6. Message Retention Policies: Kafka allows flexible configuration of message retention policies with options like time-based retention or size-based retention. RocketMQ also offers customizable retention settings based on time or size, providing flexibility for different use cases. In contrast, NSQ focuses on simplicity and defaults to a fixed retention period for messages, which can be a limitation for certain applications requiring longer retention times.

In Summary, the key differences between Apache RocketMQ, Kafka, and NSQ lie in their scalability, message delivery guarantees, community and ecosystem support, architecture and design philosophy, monitoring and management tools, and message retention policies. Each platform caters to specific use cases and requirements, offering distinct advantages for different scenarios.

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Advice on Kafka, NSQ, Apache RocketMQ

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
Kirill
Kirill

GO/C developer at Duckling Sales

Feb 16, 2021

Decided

Maybe not an obvious comparison with Kafka, since Kafka is pretty different from rabbitmq. But for small service, Rabbit as a pubsub platform is super easy to use and pretty powerful. Kafka as an alternative was the original choice, but its really a kind of overkill for a small-medium service. Especially if you are not planning to use k8s, since pure docker deployment can be a pain because of networking setup. Google PubSub was another alternative, its actually pretty cheap, but I never tested it since Rabbit was matching really good for mailing/notification services.

266k views266k
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

Detailed Comparison

Kafka
Kafka
NSQ
NSQ
Apache RocketMQ
Apache RocketMQ

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

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.

Apache RocketMQ is a distributed messaging and streaming platform with low latency, high performance and reliability, trillion-level capacity and flexible scalability.

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
support distributed topologies with no SPOF;horizontally scalable (no brokers, seamlessly add more nodes to the cluster);low-latency push based message delivery (performance);combination load-balanced and multicast style message routing;excel at both streaming (high-throughput) and job oriented (low-throughput) workloads;primarily in-memory (beyond a high-water mark messages are transparently kept on disk);runtime discovery service for consumers to find producers (nsqlookupd);transport layer security (TLS);data format agnostic;few dependencies (easy to deploy) and a sane, bounded, default configuration;simple TCP protocol supporting client libraries in any language;HTTP interface for stats, admin actions, and producers (no client library needed to publish);integrates with statsd for realtime instrumentation;robust cluster administration interface (nsqadmin)
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Statistics
GitHub Stars
31.2K
GitHub Stars
-
GitHub Stars
-
GitHub Forks
14.8K
GitHub Forks
-
GitHub Forks
-
Stacks
24.2K
Stacks
142
Stacks
48
Followers
22.3K
Followers
356
Followers
200
Votes
607
Votes
148
Votes
8
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
  • 29
    It's in golang
  • 20
    Lightweight
  • 20
    Distributed
  • 18
    Easy setup
  • 17
    High throughput
Cons
  • 1
    Long term persistence
  • 1
    HA
  • 1
    Get NSQ behavior out of Kafka but not inverse
Pros
  • 2
    Support tracing message and transactional message
  • 2
    Million-level message accumulation capacity in a single
  • 1
    Low latency
  • 1
    High throughput messaging
  • 1
    BigData Friendly
Integrations
No integrations availableNo integrations available
Docker
Docker

What are some alternatives to Kafka, NSQ, Apache RocketMQ?

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.

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.

Gearman

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.

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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