SignalR vs. Socket.IO: which one is best for you?

Before jumping into the comparison, let’s take a moment to consider why this head-to-head even makes sense.

Essentially, both Socket.IO and SignalR can be used to power realtime communication for use cases such as:

• Realtime dashboards

• Live chat and messaging apps

• Multiplayer collaboration (e.g., whiteboards)

• Realtime location updates

• In-app notifications

• Multiplayer games

• Broadcasting high-frequency updates (e.g., live score updates)

Conceptually, both technologies allow you to deliver full-duplex bidirectional updates (normally using WebSockets under the hood); however, they still have plenty of differences. 

Let’s start with a brief overview of each technology before sharpening our focus on the comparison itself. Alternatively, if you’re already well-versed in the basics, feel free to jump to the comparison.

In a nutshell, SignalR is a technology that enables you to add realtime functionality to your web application. SignalR comes in several different flavors:

• ASP.NET SignalR: A library for ASP.NET developers. Note that this version is largely outdated (only critical bugs are being fixed, but no new features are being added).

• ASP.NET Core SignalR: An open source SignalR library; unlike ASP.NET SignalR, this version is actively maintained. 

• Azure SignalR Service: The fully managed cloud version.

SignalR uses WebSocket as the main underlying transport, while providing additional features, such as:

• Automatic reconnections.

• Alternative transports (long polling and Server-Sent Events). 

• An API for creating server-to-client remote procedure calls (RPC).

• The ability to send messages to all connected clients simultaneously, or to specific (groups of) clients.   

• Hubs. A SignalR Hub is a high-level pipeline that enables connected servers and clients to invoke methods on each other.

• Multiple backplane options to choose from when scaling out ASP.NET Core SignalR: Redis, SQL Server, or Azure Service Bus (note that there’s no need to configure and manage a backplane when using the fully managed version, Azure SignalR Service). 

• Part of the ASP. NET Framework, which makes it easy to use SignalR in combination with other ASP.NET features like authentication, authorization, and dependency injection. 

• SignalR is flexible: it supports three transport protocols, and you can use for 1:1 and 1:many messaging, (as well as streaming). Additionally, SignalR supports both JSON and MessagePack as data formats.   

• SignalR offers rather weak messaging QoS; ordering and delivery are not guaranteed. You’d have to develop your own mechanism to ensure robust messaging (e.g., adding sequencing information to messages themselves). 

• SignalR offers a limited number of client SDKs: C#, Java (Android), Python, and JavaScript. There are no SDKs for languages like iOS, Android, Go, Ruby or PHP. While there is a Swift SDK, it’s experimental.

• Scaling SignalR (or any other WebSocket-based implementation) yourself is likely to be difficult, expensive, and time-consuming. You can abstract away the pain of managing SignalR yourself by using the managed version, Azure SignalR Service. However, SignalR Service also has its limitations; for example, it only provides a maximum 99.95% uptime guarantee (for premium accounts), which amounts to almost 4.5 hours of allowed downtime / unavailability per year. This SLA might not be reliable enough for critical use cases, like healthcare apps that must be available 24/7. The situation is worse for non-premium accounts, where the SLA provided is 99.9% (almost 9 hours of annual downtime).  

If you’d like to learn more about the difficulties scaling SignalR, we’ve written extensively about the key challenges and your options to overcome them.

Socket.IO is an open source realtime library that enables low-latency, bi-directional communication between web clients and servers. Built on top of the WebSocket protocol, Socket.IO provides additional capabilities compared to raw WebSockets:

• Fallback to HTTP long polling for environments where WebSockets aren’t supported (e.g., older browsers and some corporate networks with proxy servers).

• Disconnection detection, packet buffering, and automatic reconnections.

• Multiplexing (namespaces).

• Broadcasting to all clients, or a subset of clients via rooms.

• Acknowledgments (via callbacks).

• Making use of namespaces enables you to minimize the number of TCP connections used, and save socket ports on the server, while broadcasting allows you to efficiently distribute data in scenarios where you need to fan out the same message to multiple users. 

• Socket.IO is easy to get started with; it provides a simple API for both the client side and the server side, making it straightforward to implement realtime functionality into your application. 

• Integrations with various solutions for horizontal scaling: Redis, MongoDB, Postgres, AMQP / RabbitMQ, so you can choose the one that best suits your needs. Note that you must use one of these when you scale beyond a single Socket.IO server, to pass events between nodes, and ensure that events are properly routed to all clients.

• Socket.IO does not guarantee exactly-once messaging semantics. By default, Socket.IO provides an at-most-once delivery guarantee. This means there’s a chance some messages might never get delivered to recipients, especially when poor network conditions and disconnections are involved. If you’re unhappy with the default semantics, you can configure Socket.IO to provide an at-least-once messaging guarantee. However, this brings additional engineering complexity - you have to use acknowledgments, timeouts, assign a unique ID to each event, persist events in a database, and resend events upon reconnections.  

• Socket.IO offers a limited set of capabilities. Unlike other similar solutions, Socket.IO doesn’t provide features like message history, push notifications, webhooks, or serverless functions. There are only a few client and server implementations (Socket.IO is primarily a JavaScript/Node.js solution), there’s no native support for end-to-end encryption, and no Socket.IO mechanism to generate and renew tokens for authentication.

• Socket.IO is designed to work in a single region, rather than a multi-region architecture. This can lead to issues such as increased latency (if your users are in different regions), and even system downtime - what happens if the data center where you have your Socket.IO servers goes through an outage?

To learn more about the practical considerations of scaling Socket.IO, check out our guide.

Now you have a basic understanding of both SignalR, Socket.IO, and their individual advantages and limitations, let’s compare them head-on before outlining their differences and similarities.

The table below compares SignalR and Socket.IO features and capabilities:

Socket.IO is an open- source solution. In comparison, SignalR is available as an open source library (ASP.NET Core SignalR), and also as a managed, cloud-based product (Azure SignalR). 

As mentioned before, both Socket.IO and SignalR support WebSockets and HTTP long polling. However, unlike Socket.IO, SignalR also supports a third transport: Server-Sent Events. 

If you plan to use .NET on the server side, SignalR is the obvious choice (Socket.IO doesn’t even have a .NET server SDK). Comparatively, if you’re using Node.js on the server side, Socket.IO is the better option (after all, at its core, Socket.IO is a JavaScript solution). 

Since it’s part of the Microsoft/Azure ecosystem, SignalR benefits from more integrations, which makes it easier to implement things like authentication and authorization, or use serverless functions. In comparison, Socket.IO offers basically no integrations out of the box (with the notable exception of the Redis, MongoDB, and Postgres adapters, which are needed when you scale to more than one server). 

Whilst there are significant differences between them, Socket.IO and SignalR are conceptually similar.

The first similarity is that SignalR and Socket.IO are both technologies that enable a realtime, bidirectional communication channel between client and server, primarily over Web Sockets. Compared to raw sockets, SignalR and Socket.IO provide additional capabilities, such as automatic reconnections,  and fallback to HTTP long polling. 

Another similarity is that SignalR and Socket.IO both offer some flexibility in terms of messaging patterns. To be more exact, SignalR and Socket.IO can be used for 1:1 messaging, but also for 1:many data broadcast.

The third similarity worth mentioning is that SignalR (specifically ASP.NET Core SignalR) and Socket.IO are open-source solutions; their source code is freely available for developers to use. Note that for scaling ASP.NET Core SignalR and Socket.IO horizontally you need to use a tool such as Redis, so you can keep your servers in sync - this is required so that events are properly routed to all clients, even if they are connected to different servers.

The final similarity we’ll bring up in this section: SignalR and Socket.IO are designed to work in a single region, rather than in a multi-region architecture.

A single-region design can lead to issues such as:

• Increased latency: If perhaps you’re building a game or financial services platform, and latency matters to you, then you have a problem if your visitors are not near your servers. If, for example, you have two users playing a realtime game in Australia, yet your Socket.IO / SignalR servers are located in Europe, every message published will need to go halfway around the world and back.

• System downtime: What happens if the region where you have your Socket.IO / SignalR servers is unavailable? Your system would experience downtime and could become unavailable to your user base (unless you have a backup deployment, which adds engineering complexity and costs). 

Above, we looked at the features of each technology and highlighted their respective strengths and limitations. However, it's important to note that there are certain features that neither technology supports, which might be available in alternative solutions. 

Understanding these missing features will help make an informed decision, so let’s take a closer look. 

• Message ordering: Neither Socket.IO nor SignalR guarantee messages will be delivered in the order they’re sent. This might not be a problem if you’re building, say, a realtime graph, updated at such a rapid rate the user would never notice if the updates happened out of order, but for things like chat and collaborative editing where users rely on the data being delivered in a precise sequence, a lack of message ordering will lead to glitches that degrade the user’s experience.

• Exactly-once guarantees: In the world of message guarantees, there are three levels: at most once, at least once, and exactly once. The terminology is concise, but the impact on your app if messages never arrive can be lengthy. For many apps, exactly once is the ideal standard but neither WebSocket nor Socket.IO can provide it out of the box. 

• Message history: Message history (message storage, essentially) may seem trivial, but the challenge becomes harder the more complex and distributed your app is. First, will you store the messages in memory or on disk? Memory is nearly instantaneous to access, but it’s also volatile. Should your server restart as part of routine maintenance or - perish the thought - a system outage, you’ll need a way to persist those messages to disk, ideally encrypted at rest. Now imagine the downtime is caused by a data center outage. You might really regret it if you didn’t replicate your data in multiple regions to ensure data durability. Neither Socket.IO nor SingalR have a notion of message history and leave this problem for you to solve.

• Technology compatibility: On the server, SignalR is married to .NET while Socket.IO is predominantly a Node.js technology. Although there are server implementations of Socket.IO in other languages like Ruby, these are not officially supported. This lack of official support may pose challenges in production. On the client, the compatibility story is more diverse but still not totally inclusive. You may need to look further afield if you’re looking for a truly cross-platform solution.  

• Latency: Although we don't have access to any benchmarks, Socket.IO and SignalR would likely perform similarly on factors such as throughput and average latency when compared directly. While neither supports delta compression, which could potentially increase performance, achieving minimal latency primarily depends on network and platform considerations rather than the libraries themselves. As a result, neither library offers any guarantees around latency. The only way to alleviate this problem at the source is to use a hosted platform. 

As you can see in the above section, there are cases where SignalR or Socket.IO won’t be the best choice.

In these instances we recommend exploring alternative solutions to SignalR and Socket.IO that provide different or additional features.

To help you explore possible alternatives, we've written about both separately below.

• SignalR alternatives

• Socket.IO alternatives

Many of the hardest challenges, like achieving minimum latency or robust message durability, primarily depend on network and platform considerations rather than the libraries themselves. Hence, you can’t expect Socket.IO or SignalR to solve the whole equation. 

Whilst Azure SignalR might seem like the natural option if you are considering SignalR to begin with, that comes with its own disadvantages.

Even though Azure SignalR  removes some of the burden of managing realtime infrastructure, you’re restricted to a single data center for your instance. All traffic must therefore be routed through this single region, regardless of the user’s location. This has a negative impact on latency and availability - Azure only offers a 99.9% uptime SLA.

Although not part of the comparison, a more performant, capable, and reliable alternative you should consider is Ably.

Compared to Azure SignalR, Ably is globally distributed. Rather than route all traffic through one instance, data can take the shortest path through the network to achieve minimum latency. What’s more, since Ably isn’t confined to one region, a 99.999% SLA is available.

By building on Ably’s platform, developers can add capabilities they can’t with Socket.IO or SignalR like minimum latency, durable message storage, and message guarantees like predictable and exactly-once semantics. As an added benefit, push notifications, webhooks, and message history are within easy reach.

We might be biased, but we recommend you check out the documentation to see if it’s a good fit for what you’re building.