Alternatives to SignalR logo

Alternatives to SignalR

Firebase, Pusher, RabbitMQ, WebRTC, and MQTT are the most popular alternatives and competitors to SignalR.
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What is SignalR and what are its top alternatives?

SignalR allows bi-directional communication between server and client. Servers can now push content to connected clients instantly as it becomes available. SignalR supports Web Sockets, and falls back to other compatible techniques for older browsers. SignalR includes APIs for connection management (for instance, connect and disconnect events), grouping connections, and authorization.
SignalR is a tool in the Realtime Backend / API category of a tech stack.
SignalR is an open source tool with 8.8K GitHub stars and 2.3K GitHub forks. Here’s a link to SignalR's open source repository on GitHub

Top Alternatives to SignalR

  • 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. ...

  • Pusher
    Pusher

    Pusher is the category leader in delightful APIs for app developers building communication and collaboration features. ...

  • RabbitMQ
    RabbitMQ

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

  • WebRTC
    WebRTC

    It is a free, open project that enables web browsers with Real-Time Communications (RTC) capabilities via simple JavaScript APIs. The WebRTC components have been optimized to best serve this purpose. ...

  • 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. ...

  • 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... ...

  • 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. ...

  • Kafka
    Kafka

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

SignalR alternatives & related posts

Firebase logo

Firebase

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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
  • 30
    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
  • 15
    Scalability is not infinite
  • 15
    No open source, you depend on external company
  • 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 · 991.8K 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.

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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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Pusher logo

Pusher

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Hosted APIs to build realtime apps with less code
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PROS OF PUSHER
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    An easy way to give customers realtime features
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    Websockets
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    Simple
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    Easy to get started with
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    Free plan
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    Heroku Add-on
  • 11
    Easy and fast to configure and to understand
  • 9
    JSON
  • 6
    Azure Add-on
  • 6
    Happy
  • 5
    Support
  • 4
    Push notification
CONS OF PUSHER
  • 9
    Costly

related Pusher posts

Which messaging service (Pusher vs. PubNub vs. Google Cloud Pub/Sub) to use for IoT?

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Kirill Shirinkin
Cloud and DevOps Consultant at mkdev · | 3 upvotes · 306.6K views
Shared insights
on
MattermostMattermostPusherPusherTwilioTwilio
at

Recently we finished long research on chat tool for our students and mentors. In the end we picked Mattermost Team Edition as the cheapest and most feature complete option. We did consider building everything from scratch and use something like Pusher or Twilio on a backend, but then we would have to implement all the desktop and mobile clients and all the features oursevles. Mattermost gave us flexible API, lots of built in or easy to install integrations and future-proof feature set. We are still integrating it with our main platform but so far the team, existing mentors and students are very happy.

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RabbitMQ logo

RabbitMQ

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Open source multiprotocol messaging broker
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PROS OF RABBITMQ
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    It's fast and it works with good metrics/monitoring
  • 79
    Ease of configuration
  • 58
    I like the admin interface
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    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
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    Open-source
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    Delayed messages
  • 1
    Supports MQTT
  • 1
    Runs on Open Telecom Platform
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    High performance
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    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

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Yogesh Bhondekar
Product Manager | SaaS | Traveller · | 15 upvotes · 263.8K 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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WebRTC logo

WebRTC

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A free, open project that provides browsers and mobile applications with Real-Time Communications
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PROS OF WEBRTC
  • 2
    No Download
  • 2
    OpenSource
  • 1
    You can write anything around it, because it's a protoc
CONS OF WEBRTC
    Be the first to leave a con

    related WebRTC posts

    Hello. So, I wanted to make a decision on whether to use WebRTC or Amazon Chime for a conference call (meeting). My plan is to build an app with features like video broadcasting, and the ability for all the participants to talk and chat. I have used Agora's web SDK for video broadcasting, and Socket.IO for chat features. As I read the comparison between Amazon Chime and WebRTC, it further intrigues me on what I should use given my scenario? Is there any way that so many related technologies could be a hindrance to the other? Any advice would be appreciated. Thanks. Ritwik Neema

    See more
    joseph zeiad

    I am trying to implement video calling in a React Native app through Amazon Kinesis. But I was unlucky to find anything related to this on the web. Do you have any example code I can use? or any tutorial? If not, how easy is it to bridge the native library to RN? And what should I use WebRTC or Amazon Chime?? Thanks

    See more
    MQTT logo

    MQTT

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    A machine-to-machine Internet of Things connectivity protocol
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    PROS OF MQTT
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      Varying levels of Quality of Service to fit a range of
    • 1
      Very easy to configure and use with open source tools
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      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 · 24.2K 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
    gRPC logo

    gRPC

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    A high performance, open-source universal RPC framework
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    PROS OF GRPC
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      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
      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
      • 5
        Classes
      CONS OF WCF
        Be the first to leave a con

        related WCF posts

        Kafka logo

        Kafka

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        Distributed, fault tolerant, high throughput pub-sub messaging system
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        PROS OF KAFKA
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          High-throughput
        • 119
          Distributed
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          Scalable
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          High-Performance
        • 65
          Durable
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          Publish-Subscribe
        • 19
          Simple-to-use
        • 17
          Open source
        • 11
          Written in Scala and java. Runs on JVM
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          Message broker + Streaming system
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          Avro schema integration
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          Robust
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          KSQL
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          Suport Multiple clients
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          Partioned, replayable log
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          Flexible
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          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