Alternatives to MSMQ logo

Alternatives to MSMQ

Kafka, RabbitMQ, IBM MQ, Azure Service Bus, and ActiveMQ are the most popular alternatives and competitors to MSMQ.
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What is MSMQ and what are its top alternatives?

This technology enables applications running at different times to communicate across heterogeneous networks and systems that may be temporarily offline. Applications send messages to queues and read messages from queues.
MSMQ is a tool in the Message Queue category of a tech stack.

Top Alternatives to MSMQ

  • 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. ...

  • IBM MQ

    IBM MQ

    It is a messaging middleware that simplifies and accelerates the integration of diverse applications and business data across multiple platforms. It offers proven, enterprise-grade messaging capabilities that skillfully and safely move information. ...

  • Azure Service Bus

    Azure Service Bus

    It is a cloud messaging system for connecting apps and devices across public and private clouds. You can depend on it when you need highly-reliable cloud messaging service between applications and services, even when one or more is offline. ...

  • 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. ...

  • Redis

    Redis

    Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets. ...

  • MQTT

    MQTT

    It was designed as an extremely lightweight publish/subscribe messaging transport. It is useful for connections with remote locations where a small code footprint is required and/or network bandwidth is at a premium. ...

  • WCF

    WCF

    It is a framework for building service-oriented applications. Using this, you can send data as asynchronous messages from one service endpoint to another. A service endpoint can be part of a continuously available service hosted by IIS, or it can be a service hosted in an application. ...

MSMQ alternatives & related posts

Kafka logo

Kafka

15.8K
14.9K
573
Distributed, fault tolerant, high throughput pub-sub messaging system
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573
PROS OF KAFKA
  • 122
    High-throughput
  • 116
    Distributed
  • 87
    Scalable
  • 81
    High-Performance
  • 65
    Durable
  • 36
    Publish-Subscribe
  • 19
    Simple-to-use
  • 15
    Open source
  • 10
    Written in Scala and java. Runs on JVM
  • 6
    Message broker + Streaming system
  • 4
    Avro schema integration
  • 2
    Suport Multiple clients
  • 2
    Robust
  • 2
    KSQL
  • 2
    Partioned, replayable log
  • 1
    Fun
  • 1
    Extremely good parallelism constructs
  • 1
    Simple publisher / multi-subscriber model
  • 1
    Flexible
CONS OF KAFKA
  • 27
    Non-Java clients are second-class citizens
  • 26
    Needs Zookeeper
  • 7
    Operational difficulties
  • 2
    Terrible Packaging

related Kafka posts

Eric Colson
Chief Algorithms Officer at Stitch Fix · | 21 upvotes · 2.1M views

The algorithms and data infrastructure at Stitch Fix is housed in #AWS. Data acquisition is split between events flowing through Kafka, and periodic snapshots of PostgreSQL DBs. We store data in an Amazon S3 based data warehouse. Apache Spark on Yarn is our tool of choice for data movement and #ETL. Because our storage layer (s3) is decoupled from our processing layer, we are able to scale our compute environment very elastically. We have several semi-permanent, autoscaling Yarn clusters running to serve our data processing needs. While the bulk of our compute infrastructure is dedicated to algorithmic processing, we also implemented Presto for adhoc queries and dashboards.

Beyond data movement and ETL, most #ML centric jobs (e.g. model training and execution) run in a similarly elastic environment as containers running Python and R code on Amazon EC2 Container Service clusters. The execution of batch jobs on top of ECS is managed by Flotilla, a service we built in house and open sourced (see https://github.com/stitchfix/flotilla-os).

At Stitch Fix, algorithmic integrations are pervasive across the business. We have dozens of data products actively integrated systems. That requires serving layer that is robust, agile, flexible, and allows for self-service. Models produced on Flotilla are packaged for deployment in production using Khan, another framework we've developed internally. Khan provides our data scientists the ability to quickly productionize those models they've developed with open source frameworks in Python 3 (e.g. PyTorch, sklearn), by automatically packaging them as Docker containers and deploying to Amazon ECS. This provides our data scientist a one-click method of getting from their algorithms to production. We then integrate those deployments into a service mesh, which allows us to A/B test various implementations in our product.

For more info:

#DataScience #DataStack #Data

See more
John Kodumal

As we've evolved or added additional infrastructure to our stack, we've biased towards managed services. Most new backing stores are Amazon RDS instances now. We do use self-managed PostgreSQL with TimescaleDB for time-series data—this is made HA with the use of Patroni and Consul.

We also use managed Amazon ElastiCache instances instead of spinning up Amazon EC2 instances to run Redis workloads, as well as shifting to Amazon Kinesis instead of Kafka.

See more
RabbitMQ logo

RabbitMQ

14.8K
12.9K
518
Open source multiprotocol messaging broker
14.8K
12.9K
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PROS OF RABBITMQ
  • 229
    It's fast and it works with good metrics/monitoring
  • 79
    Ease of configuration
  • 58
    I like the admin interface
  • 50
    Easy to set-up and start with
  • 20
    Durable
  • 18
    Intuitive work through python
  • 18
    Standard protocols
  • 10
    Written primarily in Erlang
  • 8
    Simply superb
  • 6
    Completeness of messaging patterns
  • 3
    Scales to 1 million messages per second
  • 3
    Reliable
  • 2
    Better than most traditional queue based message broker
  • 2
    Distributed
  • 2
    Supports AMQP
  • 1
    Inubit Integration
  • 1
    Supports MQTT
  • 1
    Runs on Open Telecom Platform
  • 1
    High performance
  • 1
    Reliability
  • 1
    Clusterable
  • 1
    Clear documentation with different scripting language
  • 1
    Great ui
  • 1
    Better routing system
  • 1
    Delayed messages
CONS OF RABBITMQ
  • 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

related RabbitMQ posts

James Cunningham
Operations Engineer at Sentry · | 18 upvotes · 1.3M views
Shared insights
on
CeleryCeleryRabbitMQRabbitMQ
at

As Sentry runs throughout the day, there are about 50 different offline tasks that we execute—anything from “process this event, pretty please” to “send all of these cool people some emails.” There are some that we execute once a day and some that execute thousands per second.

Managing this variety requires a reliably high-throughput message-passing technology. We use Celery's RabbitMQ implementation, and we stumbled upon a great feature called Federation that allows us to partition our task queue across any number of RabbitMQ servers and gives us the confidence that, if any single server gets backlogged, others will pitch in and distribute some of the backlogged tasks to their consumers.

#MessageQueue

See more
Yogesh Bhondekar
Co-Founder at weconnect.chat · | 15 upvotes · 97.5K views

Hi, I am building an enhanced web-conferencing app that will have a voice/video call, live chats, live notifications, live discussions, screen sharing, etc features. Ref: Zoom.

I need advise finalizing the tech stack for this app. I am considering below tech stack:

  • Frontend: React
  • Backend: Node.js
  • Database: MongoDB
  • IAAS: #AWS
  • Containers & Orchestration: Docker / Kubernetes
  • DevOps: GitLab, Terraform
  • Brokers: Redis / RabbitMQ

I need advice at the platform level as to what could be considered to support concurrent video streaming seamlessly.

Also, please suggest what could be a better tech stack for my app?

#SAAS #VideoConferencing #WebAndVideoConferencing #zoom #stack

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IBM MQ logo

IBM MQ

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Enterprise-grade messaging middleware
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+ 1
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PROS OF IBM MQ
  • 3
    Reliable for banking transactions
  • 2
    Useful for big enteprises
  • 2
    Secure
  • 1
    Many deployment options (containers, cloud, VM etc)
  • 1
    High Availability
CONS OF IBM MQ
  • 2
    Cost

related IBM MQ posts

Azure Service Bus logo

Azure Service Bus

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344
3
Reliable cloud messaging as a service (MaaS)
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+ 1
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PROS OF AZURE SERVICE BUS
  • 2
    Cloud Native
  • 1
    Easy Integration with .Net
CONS OF AZURE SERVICE BUS
    Be the first to leave a con

    related Azure Service Bus posts

    ActiveMQ logo

    ActiveMQ

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    76
    A message broker written in Java together with a full JMS client
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    PROS OF ACTIVEMQ
    • 18
      Easy to use
    • 14
      Open source
    • 13
      Efficient
    • 10
      JMS compliant
    • 6
      High Availability
    • 5
      Scalable
    • 3
      Support XA (distributed transactions)
    • 3
      Persistence
    • 2
      Distributed Network of brokers
    • 1
      Highly configurable
    • 1
      Docker delievery
    • 0
      RabbitMQ
    CONS OF ACTIVEMQ
    • 1
      Support
    • 1
      Low resilience to exceptions and interruptions
    • 1
      Difficult to scale

    related ActiveMQ posts

    I want to choose Message Queue with the following features - Highly Available, Distributed, Scalable, Monitoring. I have RabbitMQ, ActiveMQ, Kafka and Apache RocketMQ in mind. But I am confused which one to choose.

    See more
    Naushad Warsi
    software developer at klingelnberg · | 1 upvote · 612.6K views
    Shared insights
    on
    ActiveMQActiveMQRabbitMQRabbitMQ

    I use ActiveMQ because RabbitMQ have stopped giving the support for AMQP 1.0 or above version and the earlier version of AMQP doesn't give the functionality to support OAuth.

    If OAuth is not required and we can go with AMQP 0.9 then i still recommend rabbitMq.

    See more
    Redis logo

    Redis

    43.3K
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    An in-memory database that persists on disk
    43.3K
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    3.9K
    PROS OF REDIS
    • 875
      Performance
    • 535
      Super fast
    • 511
      Ease of use
    • 441
      In-memory cache
    • 321
      Advanced key-value cache
    • 190
      Open source
    • 179
      Easy to deploy
    • 163
      Stable
    • 153
      Free
    • 120
      Fast
    • 40
      High-Performance
    • 39
      High Availability
    • 34
      Data Structures
    • 32
      Very Scalable
    • 23
      Replication
    • 20
      Great community
    • 19
      Pub/Sub
    • 17
      "NoSQL" key-value data store
    • 14
      Hashes
    • 12
      Sets
    • 10
      Sorted Sets
    • 9
      Lists
    • 8
      BSD licensed
    • 8
      NoSQL
    • 7
      Async replication
    • 7
      Integrates super easy with Sidekiq for Rails background
    • 7
      Bitmaps
    • 6
      Open Source
    • 6
      Keys with a limited time-to-live
    • 5
      Strings
    • 5
      Lua scripting
    • 4
      Awesomeness for Free!
    • 4
      Hyperloglogs
    • 3
      outstanding performance
    • 3
      Runs server side LUA
    • 3
      Networked
    • 3
      LRU eviction of keys
    • 3
      Written in ANSI C
    • 3
      Feature Rich
    • 3
      Transactions
    • 2
      Data structure server
    • 2
      Performance & ease of use
    • 1
      Existing Laravel Integration
    • 1
      Automatic failover
    • 1
      Easy to use
    • 1
      Object [key/value] size each 500 MB
    • 1
      Simple
    • 1
      Channels concept
    • 1
      Scalable
    • 1
      Temporarily kept on disk
    • 1
      Dont save data if no subscribers are found
    • 0
      Jk
    CONS OF REDIS
    • 14
      Cannot query objects directly
    • 2
      No secondary indexes for non-numeric data types
    • 1
      No WAL

    related Redis posts

    Robert Zuber

    We use MongoDB as our primary #datastore. Mongo's approach to replica sets enables some fantastic patterns for operations like maintenance, backups, and #ETL.

    As we pull #microservices from our #monolith, we are taking the opportunity to build them with their own datastores using PostgreSQL. We also use Redis to cache data we’d never store permanently, and to rate-limit our requests to partners’ APIs (like GitHub).

    When we’re dealing with large blobs of immutable data (logs, artifacts, and test results), we store them in Amazon S3. We handle any side-effects of S3’s eventual consistency model within our own code. This ensures that we deal with user requests correctly while writes are in process.

    See more

    I'm working as one of the engineering leads in RunaHR. As our platform is a Saas, we thought It'd be good to have an API (We chose Ruby and Rails for this) and a SPA (built with React and Redux ) connected. We started the SPA with Create React App since It's pretty easy to start.

    We use Jest as the testing framework and react-testing-library to test React components. In Rails we make tests using RSpec.

    Our main database is PostgreSQL, but we also use MongoDB to store some type of data. We started to use Redis  for cache and other time sensitive operations.

    We have a couple of extra projects: One is an Employee app built with React Native and the other is an internal back office dashboard built with Next.js for the client and Python in the backend side.

    Since we have different frontend apps we have found useful to have Bit to document visual components and utils in JavaScript.

    See more
    MQTT logo

    MQTT

    361
    391
    4
    A machine-to-machine Internet of Things connectivity protocol
    361
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    + 1
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    PROS OF MQTT
    • 2
      Varying levels of Quality of Service to fit a range of
    • 1
      Very easy to configure and use with open source tools
    • 1
      Lightweight with a relatively small data footprint
    CONS OF MQTT
    • 1
      Easy to configure in an unsecure manner

    related MQTT posts

    WCF logo

    WCF

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    A runtime and a set of APIs for building connected, service-oriented applications
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    PROS OF WCF
    • 2
      Classes
    CONS OF WCF
      Be the first to leave a con

      related WCF posts