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  1. Stackups
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  4. Message Queue
  5. NSQ vs RabbitMQ vs ZeroMQ

NSQ vs RabbitMQ vs ZeroMQ

OverviewDecisionsComparisonAlternatives

Overview

RabbitMQ
RabbitMQ
Stacks21.8K
Followers18.9K
Votes558
GitHub Stars13.2K
Forks4.0K
ZeroMQ
ZeroMQ
Stacks258
Followers586
Votes71
GitHub Stars10.6K
Forks2.5K
NSQ
NSQ
Stacks142
Followers356
Votes148

NSQ vs RabbitMQ vs ZeroMQ: What are the differences?

# Key Differences Between NSQ, RabbitMQ, and ZeroMQ

NSQ, RabbitMQ, and ZeroMQ are messaging systems that serve different purposes and have unique features. Understanding the key differences between them is essential for choosing the right tool for your messaging needs.

1. **Protocol Support**:
NSQ uses a custom binary protocol suited for high-throughput, real-time messaging, while RabbitMQ supports industry-standard protocols like AMQP, MQTT, and STOMP. On the other hand, ZeroMQ provides a lightweight, low-latency messaging library with support for various transports.

2. **Delivery Guarantees**:
RabbitMQ offers advanced features like reliable, persistent message delivery with acknowledgments, ensuring no message loss under normal circumstances. NSQ sacrifices guaranteed message delivery for performance and scalability, making it suitable for use cases where a few lost messages are acceptable. ZeroMQ, being a library, leaves message reliability implementation to the developer's discretion.

3. **Concurrency Model**:
NSQ is designed for horizontal scalability and fault tolerance, allowing multiple instances to run concurrently without a central message broker. RabbitMQ, on the other hand, follows a more traditional broker-based architecture, where a centralized server manages message routing. ZeroMQ's lightweight design enables easy integration with multithreaded applications for message passing without the need for an intermediary.

4. **Message Queueing Mechanism**:
RabbitMQ focuses on providing advanced message queuing features like message persistence, routing, and clustering, making it suitable for enterprise-grade applications. NSQ emphasizes simplicity and performance, with features like message partitioning and distributed routing to handle high message volumes efficiently. ZeroMQ is a lightweight library that directly connects applications for fast and efficient message exchange without the overhead of a message queue.

5. **Community and Ecosystem**:
RabbitMQ has a large community and extensive ecosystem of plugins and tools, making it suitable for a wide range of use cases with good extensibility. NSQ has a smaller but active community with a focus on performance and scalability, making it preferred for specific use cases like log collection and real-time analytics. ZeroMQ's community is known for its developer-centric nature, offering a wide range of language bindings and support for various platforms.

6. **Scalability and Flexibility**:
NSQ is built with a decentralized architecture that enables easy scaling by adding more nodes to handle increased message traffic, making it ideal for high-performance, distributed systems. RabbitMQ supports clustering for horizontal scaling but requires more configuration and management overhead compared to NSQ. ZeroMQ's lightweight design allows for flexible messaging patterns like pub-sub, pipeline, and request-reply while offering low latency and high throughput.

In Summary, understanding the key differences between NSQ, RabbitMQ, and ZeroMQ regarding protocol support, delivery guarantees, concurrency model, message queueing mechanism, community and ecosystem, as well as scalability and flexibility is crucial for selecting the most suitable messaging system for your specific requirements.

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Advice on RabbitMQ, ZeroMQ, NSQ

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
Pulkit
Pulkit

Software Engineer

Oct 30, 2020

Needs adviceonDjangoDjangoAmazon SQSAmazon SQSRabbitMQRabbitMQ

Hi! I am creating a scraping system in Django, which involves long running tasks between 1 minute & 1 Day. As I am new to Message Brokers and Task Queues, I need advice on which architecture to use for my system. ( Amazon SQS, RabbitMQ, or Celery). The system should be autoscalable using Kubernetes(K8) based on the number of pending tasks in the queue.

474k views474k
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

Detailed Comparison

RabbitMQ
RabbitMQ
ZeroMQ
ZeroMQ
NSQ
NSQ

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

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.

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.

Robust messaging for applications;Easy to use;Runs on all major operating systems;Supports a huge number of developer platforms;Open source and commercially supported
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.
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)
Statistics
GitHub Stars
13.2K
GitHub Stars
10.6K
GitHub Stars
-
GitHub Forks
4.0K
GitHub Forks
2.5K
GitHub Forks
-
Stacks
21.8K
Stacks
258
Stacks
142
Followers
18.9K
Followers
586
Followers
356
Votes
558
Votes
71
Votes
148
Pros & Cons
Pros
  • 235
    It's fast and it works with good metrics/monitoring
  • 80
    Ease of configuration
  • 60
    I like the admin interface
  • 52
    Easy to set-up and start with
  • 22
    Durable
Cons
  • 9
    Too complicated cluster/HA config and management
  • 6
    Needs Erlang runtime. Need ops good with Erlang runtime
  • 5
    Configuration must be done first, not by your code
  • 4
    Slow
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
  • 29
    It's in golang
  • 20
    Distributed
  • 20
    Lightweight
  • 18
    Easy setup
  • 17
    High throughput
Cons
  • 1
    Get NSQ behavior out of Kafka but not inverse
  • 1
    HA
  • 1
    Long term persistence

What are some alternatives to RabbitMQ, ZeroMQ, NSQ?

Kafka

Kafka

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

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.

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.

Confluent

Confluent

It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream

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