rtcStats vs ObserveRTC
ObserveRTC gives you a monitoring framework to assemble and run. rtcStats gives you an open collection layer and answers the question on top. Both are open source where it counts.
Why choose rtcStats?
The analysis is already written
A framework hands you measurements and expects you to decide what they mean. rtcStats ships the interpretation: Observations for what went wrong and Deductions for what the user experienced as a result.
Nothing to assemble first
There is no pipeline to stand up before you learn anything. Upload a session and read the result, or run rtcstats-server in your own infrastructure when you are ready to collect continuously.
Built for the tools you debug with
A REST API and an MCP server mean a session can be pulled into a script, a dashboard, or the AI assistant already open next to your editor.
At a glance
| ObserveRTC | rtcStats | |
|---|---|---|
| Delivery model | Self-hosted open source | Open-source collector plus hosted analysis |
| Open source | Yes | Yes, client and server |
| Runs in your own infrastructure | Yes | Yes, rtcstats-server |
| Commercial offering and support | No | Yes, hosted or fully on-premise |
| Client-side getStats() collection | Yes, client-monitor-js | Yes, rtcstats-js |
| Server-side aggregation across participants | Yes, observer-js | Yes, rtcstats-server |
| Automated fault detection | You define what the metrics mean | 100+ issues flagged as Observations |
| AI summary of what went wrong | No | Yes |
| MCP server | No | Yes |
| Free to run yourself | Yes | Yes, the collection layer |
Delivery model
Open source
Runs in your own infrastructure
Commercial offering and support
Client-side getStats() collection
Server-side aggregation across participants
Automated fault detection
AI summary of what went wrong
MCP server
Free to run yourself
What you get with rtcStats that you do not get from ObserveRTC
Skip building the interpretation
Two teams can look at identical getStats() output and one of them still has to work out why the call was bad. That work is a project, and it stays a project because browsers keep changing what they emit. rtcStats maintains it, so the question you are answering is what to do about the bad call rather than how to recognise one.
A timeline you can actually read
Connections, devices, streams and logs on their own views, lined up so the moment quality dropped sits beside everything else happening at that moment. There is an Experience Score for people who do not read raw stats, and you can share a session as a link with someone who has no account.
There is a company behind it
rtcStats is built and supported by three WebRTC veterans as a commercial product, so there is a roadmap, someone to email, and a deployment you can buy: hosted, or fully on-premise if your environment is closed. An open-source framework maintained around its authors' other commitments is a different kind of dependency, and worth pricing honestly before you build on one.
Frequently asked questions
- There is one real case: you want to write the analysis yourself, because your definition of a bad call is specific to your product and you would rather own that logic than adopt anyone else's. A framework you control end to end is also easier to embed in something you ship to other people. Note that keeping everything on your own infrastructure is not a reason to choose it, which is the assumption people usually arrive with: rtcStats runs fully on-premise if you need that, so the choice is about who writes the analysis rather than about where it runs.
- ObserveRTC hands you the pipeline and the metrics and expects you to decide what they mean. rtcStats hands you the same raw access and then answers the question, flagging more than a hundred quality issues automatically and saying in plain English what happened. Then there's the part of ObserveRTC being a one-man show with a dayjob and rtcStats a company of WebRTC veterans.
- Yes. The client-monitor-js and observer-js repositories are both under active development, though the pace of updates is sporadic at best.
- Yes, but why would you? Pick the one that works best for you and stick to it.
- The collection layer is. rtcstats-js and rtcstats-server are published at github.com/rtcstats/rtcstats and you can run them without sending us anything. The analysis layer, which produces Observations, Deductions, the Experience Score and the AI Summary, is a commercial hosted product.
- Yes. rtcstats-server runs in your own infrastructure and forwarding to the hosted analysis is off by default. What you send is configurable: a random sample, one user, a region, sessions that cross a quality threshold, or a single session behind a complaint.
- No. You can upload an existing dump by hand and get the full analysis back without deploying anything. That is usually the fastest way to tell whether the analysis is saying something a framework would have left you to work out.
- Collection happens in the browser through getStats(), so it does not depend on your media server. There are integration guides for LiveKit, mediasoup, Janus, Jitsi, Vonage and React Native WebRTC, plus deployment notes for common hosting.
This comparison is based on an analysis of publicly available information researched in August 2026. Products change. If something here is out of date, tell us and we will correct it.
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