Alternatives to NATS logo

Alternatives to NATS

Kafka, gRPC, MQTT, NSQ, and RabbitMQ are the most popular alternatives and competitors to NATS.
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What is NATS and what are its top alternatives?

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.
NATS is a tool in the Realtime Backend / API category of a tech stack.
NATS is an open source tool with GitHub stars and GitHub forks. Here’s a link to NATS's open source repository on GitHub

Top Alternatives to NATS

  • Kafka
    Kafka

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

  • 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... ...

  • 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. ...

  • NSQ
    NSQ

    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. ...

  • RabbitMQ
    RabbitMQ

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

  • Mosquitto
    Mosquitto

    It is lightweight and is suitable for use on all devices from low power single board computers to full servers.. The MQTT protocol provides a lightweight method of carrying out messaging using a publish/subscribe model. This makes it suitable for Internet of Things messaging such as with low power sensors or mobile devices such as phones, embedded computers or microcontrollers. ...

  • Firebase
    Firebase

    Firebase is a cloud service designed to power real-time, collaborative applications. Simply add the Firebase library to your application to gain access to a shared data structure; any changes you make to that data are automatically synchronized with the Firebase cloud and with other clients within milliseconds. ...

  • Socket.IO
    Socket.IO

    It enables real-time bidirectional event-based communication. It works on every platform, browser or device, focusing equally on reliability and speed. ...

NATS alternatives & related posts

Kafka logo

Kafka

19.7K
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Distributed, fault tolerant, high throughput pub-sub messaging system
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PROS OF KAFKA
  • 126
    High-throughput
  • 119
    Distributed
  • 90
    Scalable
  • 84
    High-Performance
  • 65
    Durable
  • 37
    Publish-Subscribe
  • 19
    Simple-to-use
  • 17
    Open source
  • 11
    Written in Scala and java. Runs on JVM
  • 8
    Message broker + Streaming system
  • 4
    Avro schema integration
  • 4
    Robust
  • 4
    KSQL
  • 2
    Suport Multiple clients
  • 2
    Partioned, replayable log
  • 1
    Flexible
  • 1
    Extremely good parallelism constructs
  • 1
    Simple publisher / multi-subscriber model
  • 1
    Fun
CONS OF KAFKA
  • 30
    Non-Java clients are second-class citizens
  • 28
    Needs Zookeeper
  • 8
    Operational difficulties
  • 3
    Terrible Packaging

related Kafka posts

Eric Colson
Chief Algorithms Officer at Stitch Fix · | 21 upvotes · 2.6M 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
gRPC logo

gRPC

1K
1.2K
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A high performance, open-source universal RPC framework
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PROS OF GRPC
  • 25
    Higth performance
  • 13
    The future of API
  • 12
    Easy setup
  • 4
    Polyglot
  • 4
    Contract-based
CONS OF GRPC
    Be the first to leave a con

    related gRPC posts

    Shared insights
    on
    gRPCgRPCSignalRSignalR.NET.NET

    We need to interact from several different Web applications (remote) to a client-side application (.exe in .NET Framework, Windows.Console under our controlled environment). From the web applications, we need to send and receive data and invoke methods to client-side .exe on javascript events like users onclick. SignalR is one of the .Net alternatives to do that, but it adds overhead for what we need. Is it better to add SignalR at both client-side application and remote web application, or use gRPC as it sounds lightest and is multilingual?

    SignalR or gRPC are always sending and receiving data on the client-side (from browser to .exe and back to browser). And web application is used for graphical visualization of data to the user. There is no need for local .exe to send or interact with remote web API. Which architecture or framework do you suggest to use in this case?

    See more
    Shared insights
    on
    KafkaKafkagRPCgRPC
    at

    By mid-2015, Uber’s rider growth coupled with its cadence of releasing new services, like Eats and Freight, was pressuring the infrastructure. To allow the decoupling of consumption from production, and to add an abstraction layer between users, developers, and infrastructure, Uber built Catalyst, a serverless internal service mesh.

    Uber decided to build their own severless solution, rather that using something like AWS Lambda, speed for its global production environments as well as introspectability.

    See more
    MQTT logo

    MQTT

    425
    510
    5
    A machine-to-machine Internet of Things connectivity protocol
    425
    510
    + 1
    5
    PROS OF MQTT
    • 3
      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

    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
    A Nielsen
    Fullstack Dev at ADTELA · | 2 upvotes · 24.5K views

    Hi Marc,

    For the com part, depending of more details not provided, i'd use SSE, OR i'd run either Mosquitto or RabbitMQ running on Amazon EC2 instances and leverage MQTT or amqp 's subscribe/publish features with my users running mqtt or amqp clients (tcp or websockets) somehow. (publisher too.. you don't say how and who gets to update the document(s).

    I find "a ton of end users", depending on how you define a ton (1k users ;) ?) and how frequent document updates are, that can mean a ton of ressources, can't cut it at some point, even using SSE

    how many, how big, how persistant do the document(s) have to be ? Db-wise,can't say for lack of details and context, yeah could also be Redis, any RDBMS or nosql or even static json files stored on an Amazon S3 bucket .. anything really

    Good luck!

    See more
    NSQ logo

    NSQ

    133
    323
    143
    A realtime distributed messaging platform
    133
    323
    + 1
    143
    PROS OF NSQ
    • 29
      It's in golang
    • 20
      Lightweight
    • 19
      Distributed
    • 18
      Easy setup
    • 16
      High throughput
    • 10
      Publish-Subscribe
    • 7
      Save data if no subscribers are found
    • 7
      Scalable
    • 6
      Open source
    • 5
      Temporarily kept on disk
    • 2
      Simple-to use
    • 1
      Load balanced
    • 1
      Free
    • 1
      Primarily in-memory
    • 1
      Topics and channels concept
    CONS OF NSQ
    • 1
      Get NSQ behavior out of Kafka but not inverse
    • 1
      Long term persistence
    • 1
      HA

    related NSQ posts

    RabbitMQ logo

    RabbitMQ

    18.2K
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    Open source multiprotocol messaging broker
    18.2K
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    PROS OF RABBITMQ
    • 232
      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
      Standard protocols
    • 18
      Intuitive work through python
    • 10
      Written primarily in Erlang
    • 8
      Simply superb
    • 6
      Completeness of messaging patterns
    • 3
      Reliable
    • 3
      Scales to 1 million messages per second
    • 2
      Better than most traditional queue based message broker
    • 2
      Distributed
    • 2
      Supports AMQP
    • 1
      Inubit Integration
    • 1
      Open-source
    • 1
      Delayed messages
    • 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
    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 · 1.5M 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
    Product Manager | SaaS | Traveller · | 15 upvotes · 264.3K 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

    See more
    Mosquitto logo

    Mosquitto

    112
    270
    14
    An open source message broker that implements the MQTT protocol
    112
    270
    + 1
    14
    PROS OF MOSQUITTO
    • 10
      Simple and light
    • 4
      Performance
    CONS OF MOSQUITTO
      Be the first to leave a con

      related Mosquitto posts

      A Nielsen
      Fullstack Dev at ADTELA · | 2 upvotes · 24.5K views

      Hi Marc,

      For the com part, depending of more details not provided, i'd use SSE, OR i'd run either Mosquitto or RabbitMQ running on Amazon EC2 instances and leverage MQTT or amqp 's subscribe/publish features with my users running mqtt or amqp clients (tcp or websockets) somehow. (publisher too.. you don't say how and who gets to update the document(s).

      I find "a ton of end users", depending on how you define a ton (1k users ;) ?) and how frequent document updates are, that can mean a ton of ressources, can't cut it at some point, even using SSE

      how many, how big, how persistant do the document(s) have to be ? Db-wise,can't say for lack of details and context, yeah could also be Redis, any RDBMS or nosql or even static json files stored on an Amazon S3 bucket .. anything really

      Good luck!

      See more
      Firebase logo

      Firebase

      34.9K
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      The Realtime App Platform
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      PROS OF FIREBASE
      • 369
        Realtime backend made easy
      • 268
        Fast and responsive
      • 240
        Easy setup
      • 212
        Real-time
      • 188
        JSON
      • 133
        Free
      • 126
        Backed by google
      • 82
        Angular adaptor
      • 67
        Reliable
      • 35
        Great customer support
      • 31
        Great documentation
      • 25
        Real-time synchronization
      • 21
        Mobile friendly
      • 18
        Rapid prototyping
      • 14
        Great security
      • 12
        Automatic scaling
      • 11
        Freakingly awesome
      • 8
        Angularfire is an amazing addition!
      • 8
        Super fast development
      • 8
        Chat
      • 6
        Firebase hosting
      • 6
        Built in user auth/oauth
      • 6
        Awesome next-gen backend
      • 6
        Ios adaptor
      • 4
        Very easy to use
      • 4
        Speed of light
      • 3
        Brilliant for startups
      • 3
        Great
      • 3
        It's made development super fast
      • 2
        Free authentication solution
      • 2
        JS Offline and Sync suport
      • 2
        Low battery consumption
      • 2
        Push notification
      • 2
        I can quickly create static web apps with no backend
      • 2
        Free hosting
      • 2
        The concurrent updates create a great experience
      • 2
        Cloud functions
      • 2
        Great all-round functionality
      • 1
        CDN & cache out of the box
      • 1
        Google's support
      • 1
        .net
      • 1
        Faster workflow
      • 1
        Free SSL
      • 1
        Easy Reactjs integration
      • 1
        Easy to use
      • 1
        Large
      • 1
        Serverless
      • 1
        Good Free Limits
      • 1
        Simple and easy
      CONS OF FIREBASE
      • 31
        Can become expensive
      • 16
        No open source, you depend on external company
      • 15
        Scalability is not infinite
      • 9
        Not Flexible Enough
      • 7
        Cant filter queries
      • 3
        Very unstable server
      • 3
        No Relational Data
      • 2
        Too many errors
      • 2
        No offline sync

      related Firebase posts

      Stephen Gheysens
      Lead Solutions Engineer at Inscribe · | 14 upvotes · 993.2K views

      Hi Otensia! I'd definitely recommend using the skills you've already got and building with JavaScript is a smart way to go these days. Most platform services have JavaScript/Node SDKs or NPM packages, many serverless platforms support Node in case you need to write any backend logic, and JavaScript is incredibly popular - meaning it will be easy to hire for, should you ever need to.

      My advice would be "don't reinvent the wheel". If you already have a skill set that will work well to solve the problem at hand, and you don't need it for any other projects, don't spend the time jumping into a new language. If you're looking for an excuse to learn something new, it would be better to invest that time in learning a new platform/tool that compliments your knowledge of JavaScript. For this project, I might recommend using Netlify, Vercel, or Google Firebase to quickly and easily deploy your web app. If you need to add user authentication, there are great examples out there for Firebase Authentication, Auth0, or even Magic (a newcomer on the Auth scene, but very user friendly). All of these services work very well with a JavaScript-based application.

      See more
      Tassanai Singprom

      This is my stack in Application & Data

      JavaScript PHP HTML5 jQuery Redis Amazon EC2 Ubuntu Sass Vue.js Firebase Laravel Lumen Amazon RDS GraphQL MariaDB

      My Utilities Tools

      Google Analytics Postman Elasticsearch

      My Devops Tools

      Git GitHub GitLab npm Visual Studio Code Kibana Sentry BrowserStack

      My Business Tools

      Slack

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      Socket.IO logo

      Socket.IO

      11.1K
      9.5K
      779
      Realtime application framework (Node.JS server)
      11.1K
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      PROS OF SOCKET.IO
      • 217
        Real-time
      • 141
        Node.js
      • 141
        Event-based communication
      • 102
        WebSockets
      • 101
        Open source
      • 26
        Binary streaming
      • 21
        No internet dependency
      • 10
        Large community
      • 9
        Fallback to polling if WebSockets not supported
      • 6
        Push notification
      • 5
        Ease of access and setup
      CONS OF SOCKET.IO
      • 11
        Bad documentation
      • 4
        Githubs that complement it are mostly deprecated
      • 3
        Doesn't work on React Native
      • 2
        Small community
      • 2
        Websocket Errors

      related Socket.IO posts

      across_the_grid
      Full-stack web developer · | 10 upvotes · 379.4K views
      Shared insights
      on
      Socket.IOSocket.IONode.jsNode.jsExpressJSExpressJS

      I use Socket.IO because the application has 2 frontend clients, which need to communicate in real-time. The backend-server handles the communication between these two clients via websockets. Socket.io is very easy to set up in Node.js and ExpressJS.

      In the research project, the 1st client shows panoramic videos in a so called cave system (it is the VR setup of our research lab, which consists of three big screens, which are specially arranged, so the user experience the videos more immersive), the 2nd client controls the videos/locations of the 1st client.

      See more

      We are starting to work on a web-based platform aiming to connect artists (clients) and professional freelancers (service providers). In-app, timeline-based, real-time communication between users (& storing it), file transfers, and push notifications are essential core features. We are considering using Node.js, ExpressJS, React, MongoDB stack with Socket.IO & Apollo, or maybe using Real-Time Database and functionalities of Firebase.

      See more