Alternatives to ZeroMQ logo

Alternatives to ZeroMQ

RabbitMQ, Kafka, MQTT, Redis, and ActiveMQ are the most popular alternatives and competitors to ZeroMQ.
260
582
+ 1
71

What is ZeroMQ and what are its top alternatives?

ZeroMQ is a high-performance messaging library that provides sockets for communication between applications. It is designed for use in distributed systems and supports various messaging patterns like pub/sub, request/reply, and push/pull. ZeroMQ is lightweight, easy to use, and language-agnostic, making it suitable for a wide range of applications. However, setting up a ZeroMQ infrastructure can be complex and may require additional effort to ensure proper functioning.

  1. NATS: NATS is a fast, secure, and lightweight messaging system that provides high-performance communication. It supports multiple messaging patterns and is easy to deploy and scale. Pros include simplicity, scalability, and high performance. Cons compared to ZeroMQ include less flexibility in messaging patterns and fewer advanced features.

  2. RabbitMQ: RabbitMQ is a popular open-source message broker that supports multiple messaging protocols such as AMQP and MQTT. It provides features like clustering, routing, and message persistence. Pros include robustness, reliability, and a large community. Cons compared to ZeroMQ include higher resource consumption and complexity in setting up.

  3. Kafka: Apache Kafka is a distributed streaming platform that is commonly used for building real-time data pipelines and stream processing applications. It provides high throughput, horizontal scalability, and fault tolerance. Pros include fault tolerance, scalability, and support for stream processing. Cons compared to ZeroMQ include higher latency and complexity in deployment.

  4. Redis: Redis is an open-source in-memory data structure store that can be used as a message broker. It supports pub/sub messaging and provides high performance and low latency. Pros include simplicity, low latency, and persistence. Cons compared to ZeroMQ include limited message queuing capabilities and lack of advanced messaging patterns.

  5. ActiveMQ: Apache ActiveMQ is a popular message broker that supports multiple messaging protocols like AMQP, STOMP, and MQTT. It provides features like clustering, failover, and message persistence. Pros include flexibility, reliability, and support for various messaging protocols. Cons compared to ZeroMQ include higher resource consumption and complexity in configuration.

  6. MQTT: MQTT is a lightweight messaging protocol designed for IoT and mobile applications. It provides low bandwidth usage, low latency, and support for quality of service levels. Pros include simplicity, low overhead, and support for constrained environments. Cons compared to ZeroMQ include limited message queuing capabilities and lack of advanced messaging patterns.

  7. RocketMQ: Apache RocketMQ is a scalable and reliable messaging system that is suitable for high-throughput applications. It provides features like message ordering, transactional messaging, and batch processing. Pros include scalability, reliability, and support for advanced messaging features. Cons compared to ZeroMQ include complexity in deployment and higher resource consumption.

  8. HornetQ: HornetQ is a open-source message broker that provides high performance and scalability. It supports features like clustering, load balancing, and message persistence. Pros include performance, scalability, and support for various messaging patterns. Cons compared to ZeroMQ include complexity in configuration and lack of language bindings.

  9. Pulsar: Apache Pulsar is a distributed messaging system that provides low-latency, high-throughput messaging. It supports features like geo-replication, tiered storage, and multi-tenancy. Pros include scalability, performance, and advanced features. Cons compared to ZeroMQ include complexity in deployment and additional overhead for managing the system.

  10. KubeMQ: KubeMQ is a Kubernetes-native messaging system that provides secure and reliable messaging for microservices. It supports features like pub/sub messaging, request/reply, and event-driven architecture. Pros include seamless integration with Kubernetes, simplicity, and support for modern application architectures. Cons compared to ZeroMQ include dependency on Kubernetes for deployment and potential resource overhead.

Top Alternatives to ZeroMQ

  • RabbitMQ
    RabbitMQ

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

  • Kafka
    Kafka

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

  • 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. ...

  • Redis
    Redis

    Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams. ...

  • 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. ...

  • nanomsg
    nanomsg

    It is a socket library that provides several common communication patterns. It aims to make the networking layer fast, scalable, and easy to use. Implemented in C, it works on a wide range of operating systems with no further dependencies. ...

  • gRPC
    gRPC

    gRPC is a modern open source high performance RPC framework that can run in any environment. It can efficiently connect services in and across data centers with pluggable support for load balancing, tracing, health checking... ...

  • NATS
    NATS

    Unlike traditional enterprise messaging systems, NATS has an always-on dial tone that does whatever it takes to remain available. This forms a great base for building modern, reliable, and scalable cloud and distributed systems. ...

ZeroMQ alternatives & related posts

RabbitMQ logo

RabbitMQ

21K
18.4K
527
Open source multiprotocol messaging broker
21K
18.4K
+ 1
527
PROS OF RABBITMQ
  • 234
    It's fast and it works with good metrics/monitoring
  • 79
    Ease of configuration
  • 59
    I like the admin interface
  • 50
    Easy to set-up and start with
  • 21
    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
    Distributed
  • 2
    Supports MQTT
  • 2
    Better than most traditional queue based message broker
  • 2
    Supports AMQP
  • 1
    Clusterable
  • 1
    Clear documentation with different scripting language
  • 1
    Great ui
  • 1
    Inubit Integration
  • 1
    Better routing system
  • 1
    High performance
  • 1
    Runs on Open Telecom Platform
  • 1
    Delayed messages
  • 1
    Reliability
  • 1
    Open-source
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 · 1.7M 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

Around the time of their Series A, Pinterest’s stack included Python and Django, with Tornado and Node.js as web servers. Memcached / Membase and Redis handled caching, with RabbitMQ handling queueing. Nginx, HAproxy and Varnish managed static-delivery and load-balancing, with persistent data storage handled by MySQL.

See more
Kafka logo

Kafka

23.1K
21.7K
607
Distributed, fault tolerant, high throughput pub-sub messaging system
23.1K
21.7K
+ 1
607
PROS OF KAFKA
  • 126
    High-throughput
  • 119
    Distributed
  • 92
    Scalable
  • 86
    High-Performance
  • 66
    Durable
  • 38
    Publish-Subscribe
  • 19
    Simple-to-use
  • 18
    Open source
  • 12
    Written in Scala and java. Runs on JVM
  • 9
    Message broker + Streaming system
  • 4
    KSQL
  • 4
    Avro schema integration
  • 4
    Robust
  • 3
    Suport Multiple clients
  • 2
    Extremely good parallelism constructs
  • 2
    Partioned, replayable log
  • 1
    Simple publisher / multi-subscriber model
  • 1
    Fun
  • 1
    Flexible
CONS OF KAFKA
  • 32
    Non-Java clients are second-class citizens
  • 29
    Needs Zookeeper
  • 9
    Operational difficulties
  • 5
    Terrible Packaging

related Kafka posts

Nick Rockwell
SVP, Engineering at Fastly · | 46 upvotes · 3.5M views

When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?

So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.

React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.

Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.

See more
Ashish Singh
Tech Lead, Big Data Platform at Pinterest · | 38 upvotes · 3M views

To provide employees with the critical need of interactive querying, we’ve worked with Presto, an open-source distributed SQL query engine, over the years. Operating Presto at Pinterest’s scale has involved resolving quite a few challenges like, supporting deeply nested and huge thrift schemas, slow/ bad worker detection and remediation, auto-scaling cluster, graceful cluster shutdown and impersonation support for ldap authenticator.

Our infrastructure is built on top of Amazon EC2 and we leverage Amazon S3 for storing our data. This separates compute and storage layers, and allows multiple compute clusters to share the S3 data.

We have hundreds of petabytes of data and tens of thousands of Apache Hive tables. Our Presto clusters are comprised of a fleet of 450 r4.8xl EC2 instances. Presto clusters together have over 100 TBs of memory and 14K vcpu cores. Within Pinterest, we have close to more than 1,000 monthly active users (out of total 1,600+ Pinterest employees) using Presto, who run about 400K queries on these clusters per month.

Each query submitted to Presto cluster is logged to a Kafka topic via Singer. Singer is a logging agent built at Pinterest and we talked about it in a previous post. Each query is logged when it is submitted and when it finishes. When a Presto cluster crashes, we will have query submitted events without corresponding query finished events. These events enable us to capture the effect of cluster crashes over time.

Each Presto cluster at Pinterest has workers on a mix of dedicated AWS EC2 instances and Kubernetes pods. Kubernetes platform provides us with the capability to add and remove workers from a Presto cluster very quickly. The best-case latency on bringing up a new worker on Kubernetes is less than a minute. However, when the Kubernetes cluster itself is out of resources and needs to scale up, it can take up to ten minutes. Some other advantages of deploying on Kubernetes platform is that our Presto deployment becomes agnostic of cloud vendor, instance types, OS, etc.

#BigData #AWS #DataScience #DataEngineering

See more
MQTT logo

MQTT

597
571
7
A machine-to-machine Internet of Things connectivity protocol
597
571
+ 1
7
PROS OF MQTT
  • 3
    Varying levels of Quality of Service to fit a range of
  • 2
    Lightweight with a relatively small data footprint
  • 2
    Very easy to configure and use with open source tools
CONS OF MQTT
  • 1
    Easy to configure in an unsecure manner

related MQTT posts

Kindly suggest the best tool for generating 10Mn+ concurrent user load. The tool must support MQTT traffic, REST API, support to interfaces such as Kafka, websockets, persistence HTTP connection, auth type support to assess the support /coverage.

The tool can be integrated into CI pipelines like Azure Pipelines, GitHub, and Jenkins.

See more
Reza Saadat
IoT Solutions Architect at GreenEdge · | 5 upvotes · 87.1K views
Shared insights
on
MQTTMQTTNATSNATS

I want to use NATS for my IoT Platform and replace it instead of the MQTT broker. is there any preferred added value to do that?

See more
Redis logo

Redis

58.4K
45K
3.9K
Open source (BSD licensed), in-memory data structure store
58.4K
45K
+ 1
3.9K
PROS OF REDIS
  • 886
    Performance
  • 542
    Super fast
  • 513
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
  • 194
    Open source
  • 182
    Easy to deploy
  • 164
    Stable
  • 155
    Free
  • 121
    Fast
  • 42
    High-Performance
  • 40
    High Availability
  • 35
    Data Structures
  • 32
    Very Scalable
  • 24
    Replication
  • 22
    Great community
  • 22
    Pub/Sub
  • 19
    "NoSQL" key-value data store
  • 16
    Hashes
  • 13
    Sets
  • 11
    Sorted Sets
  • 10
    NoSQL
  • 10
    Lists
  • 9
    Async replication
  • 9
    BSD licensed
  • 8
    Bitmaps
  • 8
    Integrates super easy with Sidekiq for Rails background
  • 7
    Keys with a limited time-to-live
  • 7
    Open Source
  • 6
    Lua scripting
  • 6
    Strings
  • 5
    Awesomeness for Free
  • 5
    Hyperloglogs
  • 4
    Transactions
  • 4
    Outstanding performance
  • 4
    Runs server side LUA
  • 4
    LRU eviction of keys
  • 4
    Feature Rich
  • 4
    Written in ANSI C
  • 4
    Networked
  • 3
    Data structure server
  • 3
    Performance & ease of use
  • 2
    Dont save data if no subscribers are found
  • 2
    Automatic failover
  • 2
    Easy to use
  • 2
    Temporarily kept on disk
  • 2
    Scalable
  • 2
    Existing Laravel Integration
  • 2
    Channels concept
  • 2
    Object [key/value] size each 500 MB
  • 2
    Simple
CONS OF REDIS
  • 15
    Cannot query objects directly
  • 3
    No secondary indexes for non-numeric data types
  • 1
    No WAL

related Redis posts

Russel Werner
Lead Engineer at StackShare · | 32 upvotes · 2.5M views

StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.

Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!

#StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit

See more
Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.6M views

Our whole DevOps stack consists of the following tools:

  • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively Git as revision control system
  • SourceTree as Git GUI
  • Visual Studio Code as IDE
  • CircleCI for continuous integration (automatize development process)
  • Prettier / TSLint / ESLint as code linter
  • SonarQube as quality gate
  • Docker as container management (incl. Docker Compose for multi-container application management)
  • VirtualBox for operating system simulation tests
  • Kubernetes as cluster management for docker containers
  • Heroku for deploying in test environments
  • nginx as web server (preferably used as facade server in production environment)
  • SSLMate (using OpenSSL) for certificate management
  • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
  • PostgreSQL as preferred database system
  • Redis as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

  • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
  • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
  • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
  • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
  • Scalability: All-in-one framework for distributed systems.
  • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
See more
ActiveMQ logo

ActiveMQ

608
1.3K
77
A message broker written in Java together with a full JMS client
608
1.3K
+ 1
77
PROS OF ACTIVEMQ
  • 18
    Easy to use
  • 14
    Open source
  • 13
    Efficient
  • 10
    JMS compliant
  • 6
    High Availability
  • 5
    Scalable
  • 3
    Distributed Network of brokers
  • 3
    Persistence
  • 3
    Support XA (distributed transactions)
  • 1
    Docker delievery
  • 1
    Highly configurable
  • 0
    RabbitMQ
CONS OF ACTIVEMQ
  • 1
    ONLY Vertically Scalable
  • 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 · 779.6K 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
nanomsg logo

nanomsg

10
29
0
A socket library
10
29
+ 1
0
PROS OF NANOMSG
    Be the first to leave a pro
    CONS OF NANOMSG
      Be the first to leave a con

      related nanomsg posts

      gRPC logo

      gRPC

      2.1K
      1.3K
      63
      A high performance, open-source universal RPC framework
      2.1K
      1.3K
      + 1
      63
      PROS OF GRPC
      • 24
        Higth performance
      • 15
        The future of API
      • 13
        Easy setup
      • 5
        Contract-based
      • 4
        Polyglot
      • 2
        Garbage
      CONS OF GRPC
        Be the first to leave a con

        related gRPC posts

        Noah Zoschke
        Engineering Manager at Segment · | 30 upvotes · 270.2K views

        We just launched the Segment Config API (try it out for yourself here) — a set of public REST APIs that enable you to manage your Segment configuration. Behind the scenes the Config API is built with Go , GRPC and Envoy.

        At Segment, we build new services in Go by default. The language is simple so new team members quickly ramp up on a codebase. The tool chain is fast so developers get immediate feedback when they break code, tests or integrations with other systems. The runtime is fast so it performs great at scale.

        For the newest round of APIs we adopted the GRPC service #framework.

        The Protocol Buffer service definition language makes it easy to design type-safe and consistent APIs, thanks to ecosystem tools like the Google API Design Guide for API standards, uber/prototool for formatting and linting .protos and lyft/protoc-gen-validate for defining field validations, and grpc-gateway for defining REST mapping.

        With a well designed .proto, its easy to generate a Go server interface and a TypeScript client, providing type-safe RPC between languages.

        For the API gateway and RPC we adopted the Envoy service proxy.

        The internet-facing segmentapis.com endpoint is an Envoy front proxy that rate-limits and authenticates every request. It then transcodes a #REST / #JSON request to an upstream GRPC request. The upstream GRPC servers are running an Envoy sidecar configured for Datadog stats.

        The result is API #security , #reliability and consistent #observability through Envoy configuration, not code.

        We experimented with Swagger service definitions, but the spec is sprawling and the generated clients and server stubs leave a lot to be desired. GRPC and .proto and the Go implementation feels better designed and implemented. Thanks to the GRPC tooling and ecosystem you can generate Swagger from .protos, but it’s effectively impossible to go the other way.

        See more
        Dylan Krupp
        Shared insights
        on
        gRPCgRPCGraphQLGraphQL

        I used GraphQL extensively at a previous employer a few years ago and really appreciated the data-driven schema etc alongside the many other benefits it provided. At that time, it seemed like it was set to replace RESTful APIs and many companies were adopting it.

        However, as of late, it seems like interest has been waning for GraphQL as opposed to increasing as I had assumed it would. Am I missing something here? What is the current perspective regarding this technology?

        Currently, I'm working with gRPC and was curious as to the state of everything now.

        See more
        NATS logo

        NATS

        368
        489
        60
        Lightweight publish-subscribe & distributed queueing messaging system
        368
        489
        + 1
        60
        PROS OF NATS
        • 22
          Fastest pub-sub system out there
        • 16
          Rock solid
        • 12
          Easy to grasp
        • 4
          Light-weight
        • 4
          Easy, Fast, Secure
        • 2
          Robust Security Model
        CONS OF NATS
        • 2
          Persistence with Jetstream supported
        • 1
          No Order
        • 1
          No Persistence

        related NATS posts

        Go is a high performance language with simple syntax / semantics. Although it is not as expressive as some other languages, it's still a great language for backend development.

        Python is expressive and battery-included, and pre-installed in most linux distros, making it a great language for scripting.

        PostgreSQL: Rock-solid RDBMS with NoSQL support.

        TypeScript saves you from all nonsense semantics of JavaScript , LOL.

        NATS: fast message queue and easy to deploy / maintain.

        Docker makes deployment painless.

        Git essential tool for collaboration and source management.

        See more
        Reza Saadat
        IoT Solutions Architect at GreenEdge · | 5 upvotes · 87.1K views
        Shared insights
        on
        MQTTMQTTNATSNATS

        I want to use NATS for my IoT Platform and replace it instead of the MQTT broker. is there any preferred added value to do that?

        See more