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  1. Stackups
  2. Utilities
  3. Background Jobs
  4. Message Queue
  5. BlazingMQ vs NSQ

BlazingMQ vs NSQ

OverviewComparisonAlternatives

Overview

NSQ
NSQ
Stacks141
Followers356
Votes148
BlazingMQ
BlazingMQ
Stacks0
Followers5
Votes0
GitHub Stars3.0K
Forks155

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Detailed Comparison

NSQ
NSQ
BlazingMQ
BlazingMQ

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.

It is an open-source distributed message queueing framework, which focuses on efficiency, reliability, and a rich feature set for modern-day workflows.

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)
Message routing strategies; Subscriptions; Poison pill detection; Compression; Consistency levels; Consumer flow control; Distributed trace; Host health monitoring
Statistics
GitHub Stars
-
GitHub Stars
3.0K
GitHub Forks
-
GitHub Forks
155
Stacks
141
Stacks
0
Followers
356
Followers
5
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
Docker
Docker
Python
Python
Java
Java
C++
C++

What are some alternatives to NSQ, BlazingMQ?

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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