We have recently noticed an influx of individuals searching for alternatives to building chat messaging applications on Firebase. It's important to note that Firebase is a multi-use tool for developers to build just about anything quickly, but does not take into account the cost when an application starts to scale in terms of users. In contrast, Stream provides a chat messaging API (as well as SDKs) and the necessary underlying infrastructure for building a real-time messaging chat application.
Chat Messaging APIs
Stream is one of the leading providers in the chat API market, alongside players like Sendbird, CometChat, and Agora. While general-purpose platforms like Twilio Conversations, AWS AppSync, and Azure Communication Services exist, specialized providers such as Stream deliver the depth of features and scalability required for production-grade chat.
There are pros and cons to each player. However, in this post, we'll discussthe many features that users of chat messaging applications expect, how Stream provides those features out of the box, and where Firebase falls short.
In-House Chat Solutions
You can build an in-house chat system on many stacks. For larger-scale applications, teams often choose performance-oriented languages such as Go or Java (and Rust for systems-level components) when low latency and high concurrency are priorities. Given the large-scale applications deployed on Stream's Chat infrastructure, our team chose Go for its simple concurrency model and operational ease. To support scalability and fault tolerance, we pair our services with RocksDB for low-latency storage and Raft for consensus and replication, both widely used and battle-tested.
If you're building an in-house solution for chat, developers commonly choose Socket.io or Firebase. Socket.io provides the real-time portion of chat, but does not scale with an influx of users without throwing more memory hogging machines at it. Additionally, Socket.io does not offer additional features out of the box, such as data-persistence.
Firebase, on the other hand, will take care of both real-time as well as data persistence; however, scaling with the application's user base often becomes a cost issue rather than an infrastructure issue.
Features of a Chat API
Consumers are accustomed to and expect a highly polished chat experience. Applications such as WhatsApp, Slack, Facebook Messenger, and iMessage are well-known and commonly used within households and work environments. The applications mentioned above have focused many years of development and customer research on building rich and interactive chat experiences for unique use cases and the masses.
Generally speaking, because real-time chat has become so popular among individuals, many features are expected to be available because it is the new standard. Below is a shortlist of the most common features that applications implement:
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Typing indicators: Show when the user is typing
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URL previews: Show an image, text-description, or video when adding a URL in a chat message
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User presence: Show who is online
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Reactions & Threads: Support modern messaging best practices such as reactions and threads
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Unread counts: Show the number of unread messages that need attention
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Offline storage: Keep the chat working, even if the network connection is unstable (an important feature of mobile apps in particular)
The above bullet points are only a small subset of the number of features available in most chat applications. Here's the full list that Stream Chat provides out of the box:
If you compare the feature set of Firebase to Stream Chat, you will quickly notice that Firebase does not offer as many of the features that Stream Chat provides out of the box.
Firebase gives you the building blocks for real-time sync, and with Firestore + Cloud Functions, you can create some basic chat functionality. But features like threads, reactions, moderation tools, typing indicators, and offline sync require custom development.
The result? Building a fully-featured chat API on top of Firebase requires a significant amount of development overhead, equating to an unknown amount of time to get to market.
Comparatively, Stream provides these chat features out of the box, so you can move faster without reinventing the wheel.
Should time not be an issue and you don't need a lot of features, Firebase may seem like a simple approach to get your application off the ground. However, developers often fail to understand that building features that may look easy -- such as unread counts -- is possible, but will eventually turn into a mess when it's time to scale. Stream Chat focuses on providing an efficient approach for developers to build a custom chat application faster and scale by leveraging every feature within the Stream Chat API that has been carefully thought out.
When to Use Firebase for Chat
If you intend to use Firebase for chat, keep in mind that you need to invest in a significant amount of upfront development -- and we all know that comes at a high cost. Firebase is, for the most part, intended for smaller applications. On that note, building chat on top of Firebase will quickly drive your team into a combination of technical and cost-related issues, especially as your user base grows. For example, there is a maximum hard number of 200,000 concurrent connections on Firebase, whereas Stream does not impose any limits on this number.
Firebase can be a valid option for some teams, though. It may make sense if:
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You're not paying for your developer's time. (e.g., you are two co-founders working on a new business, or someone working on a hackathon, etc.)
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Your chat use case is basic, and you don't expect the usage of chat to grow.
Firebase is generally not a good fit if:
- You need to sync significant development into your application to build most basic chat features, and are worried about the scalability of your chat application as the user base grows.
Simply put, as you scale, it becomes more problematic and expensive than using a proven chat API provider, so you will never recoup your upfront investment that occurred during development.
Stream vs Firebase
While Firebase has an API and various SDKs to accommodate any coding language, it does not offer help on the UI/UX side. Furthermore, Firebase does not specifically cater to applications within the chat ecosystem, so you will be left in the dark when it comes to building out features from scratch.
If you are building a chat focused application on top of Stream Chat's API, Stream provides SDKs and UI kits for React, React Native, Flutter, Swift, Unity, Angular, Unreal, and Kotlin. Stream has built additional products to improve the speed of taking your product from ideation to reality, allowing your team to significantly reduce the build time required to get your application in the hands of users.
Final Thoughts
Building chat in-house is a complicated and expensive process. While you can use Socket.io or Firebase as your platform to build on top of, you will undoubtedly run into issues related to scalability and performance and, more importantly, the cost that can hinder your business as a whole or potentially cause it to fail.
There are various API-driven chat products on the market, and they were all built for specific reasons around different business models. In my opinion, Stream is at the forefront of innovation as a company, as we take in every idea that developers and teams around the world provide to us in the form of feedback. We also believe that supporting our customers is fundamental, and we do that by providing them with the absolute best service and transparency possible.
It's always important to weigh your options when building a product around any technology, whether it's an open-source technology or a paid infrastructure driven by an API. Stream Chat outweighs the competition from every angle, including transparent pricing, extreme scalability, high-touch support, and a unique feature set. Hopefully, this shows why Stream is not only an alternative to Firebase, but also a much more complete solution for your messaging needs.