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  1. Stackups
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  4. Message Queue
  5. Hutch vs NSQ

Hutch vs NSQ

OverviewDecisionsComparisonAlternatives

Overview

NSQ
NSQ
Stacks141
Followers356
Votes148
Hutch
Hutch
Stacks7
Followers9
Votes0

Hutch vs NSQ: What are the differences?

Introduction:

Hutch and NSQ are both messaging platforms widely used for distributed systems communication. While they serve similar purposes, they have key differences that set them apart from each other.

1. Message Delivery Mechanism: Hutch utilizes a push-based message delivery mechanism, where messages are immediately pushed to the subscribers when they become available. On the other hand, NSQ employs a pull-based model, where subscribers actively pull messages from the queue when they are ready to process them.

2. Scalability: NSQ is designed with scalability in mind, offering features like horizontal scaling and distributed queues that make it suitable for handling large volumes of messages across multiple nodes. In contrast, Hutch is optimized for simpler architectures and may not scale as effectively in high-demand scenarios.

3. Ecosystem Integration: NSQ integrates seamlessly with various cloud services and containers, enabling easy deployment and management in cloud environments. Hutch, on the other hand, may require more manual configuration and setup when integrating with cloud-based ecosystems.

4. Fault Tolerance: NSQ provides built-in fault tolerance mechanisms such as message re-queuing and redundancy options to ensure message delivery reliability in case of failures. Hutch, while robust, may require additional customization and setup to achieve similar levels of fault tolerance.

5. Configuration Complexity: Hutch emphasizes simplicity and ease of use, offering straightforward configuration options that cater to smaller projects and teams. NSQ, in comparison, may have a steeper learning curve due to its extensive configuration settings and advanced features tailored for complex distributed systems.

6. Community Support: NSQ boasts a strong community of developers and contributors actively maintaining and improving the platform, providing regular updates, bug fixes, and support. Hutch, while supported by its developer team, may have a relatively smaller community presence and fewer resources available for troubleshooting and evolving the platform.

In Summary, Hutch and NSQ differ in message delivery mechanisms, scalability, ecosystem integration, fault tolerance, configuration complexity, and community support, offering distinct advantages and considerations for developers based on their specific requirements.

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Advice on NSQ, Hutch

Pramod
Pramod

Co Founder at Usability Designs

Mar 2, 2020

Needs advice

I am looking into IoT World Solution where we have MQTT Broker. This MQTT Broker Sits in one of the Data Center. We are doing a lot of Alert and Alarm related processing on that Data, Currently, we are looking into Solution which can do distributed persistence of log/alert primarily on remote Disk.

Our primary need is to use lightweight where operational complexity and maintenance costs can be significantly reduced. We want to do it on-premise so we are not considering cloud solutions.

We looked into the following alternatives:

Apache Kafka - Great choice but operation and maintenance wise very complex. Rabbit MQ - High availability is the issue, Apache Pulsar - Operational Complexity. NATS - Absence of persistence. Akka Streams - Big learning curve and operational streams.

So we are looking into a lightweight library that can do distributed persistence preferably with publisher and subscriber model. Preferable on JVM stack.

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Comments

Detailed Comparison

NSQ
NSQ
Hutch
Hutch

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.

Hutch is a Ruby library for enabling asynchronous inter-service communication in a service-oriented architecture, using RabbitMQ.

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)
A simple way to define consumers (queues are automatically created and bound to the exchange with the appropriate binding keys);An executable and CLI for running consumers (akin to rake resque:work);Automatic setup of the central exchange;Sensible out-of-the-box configuration (e.g. durable messages, persistent queues, message acknowledgements);Management of queue subscriptions;Rails integration;Configurable exception handling
Statistics
Stacks
141
Stacks
7
Followers
356
Followers
9
Votes
148
Votes
0
Pros & Cons
Pros
  • 29
    It's in golang
  • 20
    Distributed
  • 20
    Lightweight
  • 18
    Easy setup
  • 17
    High throughput
Cons
  • 1
    Long term persistence
  • 1
    Get NSQ behavior out of Kafka but not inverse
  • 1
    HA
No community feedback yet
Integrations
No integrations available
RabbitMQ
RabbitMQ

What are some alternatives to NSQ, Hutch?

Kafka

Kafka

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

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.

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