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How collaborative cursors and presence work
A collaborative editor usually handles two related but distinct kinds of shared state:
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- Document content: edits that belong to the shared document and need to remain available as the document changes over time.
- Presence or awareness: temporary UI state such as a participant’s cursor, selection, identity, avatar or online status. It is useful while people are working together, but does not need to become part of the saved document.
Yjs Awareness is separate from persisted Yjs document content. Its documentation explains that awareness information is not stored in the Yjs document because it does not need to persist across sessions. Liveblocks similarly describes Presence as temporary state that disappears when a connection ends. See the Yjs Awareness & Presence documentation and Liveblocks’ Presence documentation for their respective models.
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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallSeparating these streams matters operationally: cursor movement can be frequent and transient, whereas document edits have different persistence and synchronization requirements. An editor should not treat every cursor update as a durable document edit.
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What the protocol timers mean
Yjs Awareness uses client IDs, increasing clocks and per-client states. A newer clock supersedes a previously known state; a null state marks a client offline. The Yjs Awareness API documentation describes a 30-second stale timeout. The y-protocols awareness specification also says clients should rebroadcast at least every 15 seconds and that a peer should be removed locally after 30 seconds without an update.
These are liveness and stale-state rules, not recommendations to refresh a visible cursor only every 15 seconds. A product’s cursor responsiveness is a separate design decision. The protocol figures describe Yjs behavior, not an industry-wide timer standard.
Why fan-out has no universal participant ceiling
In a room-wide broadcast design, one participant’s awareness update is distributed to other subscribed participants. A useful planning heuristic for a simple unfiltered broadcast is:
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Aggregate delivery work ≈ active publishers × updates per second × recipients per update × average payload size.
This is arithmetic for reasoning about workload, not a benchmark or a performance law. It shows why a small cursor payload can still create substantial aggregate traffic: more publishers, more frequent updates or more recipients increase the amount of data delivered. Actual cost also depends on message processing, routing and rendering; the arithmetic does not predict a particular server’s capacity.
Yjs’ WebSocket provider documentation describes a client-server model that distributes document updates and awareness among connected clients. Yjs also cautions that the same shared document may be handled by multiple servers. That is a topology consideration, not a documented room-size ceiling. Capacity therefore has at least three separate boundaries:
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- Protocol behavior: how updates are ordered and stale peers are handled.
- Service limits: an explicit cap imposed by a particular hosted product or plan.
- System capacity: the workload-specific point at which latency, CPU, bandwidth, memory or client rendering degrades.
The sources establish Yjs protocol behavior and one hosted provider’s published room limits; they do not establish a universal maximum room size or a general cursor-capacity benchmark.
How often should cursor positions update?
There is no supported universal rate in the available documentation. A hosted product’s throttle is a useful implementation-specific reference, but not a blanket recommendation for every editor, network or payload.
Liveblocks’ documented throttle
Liveblocks documents a default WebSocket message throttle of 100 milliseconds, configurable from 16 to 1000 milliseconds. Its tutorial describes 16 milliseconds as approximately 60 frames per second. Those are Liveblocks client settings; they do not establish an ideal rate for all systems. Faster publication can make cursor animation feel smoother, while increasing outbound and downstream message work.
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Choose a rate for the experience and workload
Decide what a user must perceive—such as smooth pointer movement or timely selection changes—then test the publication behavior against the actual payload, recipient scope, network conditions and rendering budget. Consider coalescing intermediate pointer positions, skipping unchanged state, limiting updates for off-screen participants, or subscribing clients only to relevant scopes. These are design options to evaluate, not guaranteed optimizations.
What a hosted room cap does—and does not—tell you
Liveblocks’ published plan limits list the following maximum simultaneous connections per room, accessed October 5, 2026:
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| Liveblocks plan | Simultaneous connections per room |
|---|---|
| Free | 10 |
| Pro | 10 |
| Team | 50 |
| Enterprise | 100 |
Liveblocks’ maximum-capacity guide says additional users cannot join once a room reaches the cap. These are product- and plan-specific service constraints, not the physical maximum for every editor architecture. Plan terms can change, so verify the provider’s current limits before making a deployment decision.
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How to compare self-managed and hosted approaches
Yjs is a data framework; a self-managed Yjs provider leaves operational responsibilities with the application team. Liveblocks offers hosted synchronization and a Yjs provider, and its integration exposes Liveblocks Presence as Yjs awareness. The evidence here does not provide an apples-to-apples performance benchmark, so the choice should follow workload and operational requirements rather than an unsupported capacity ranking.
| Decision area | Questions to resolve |
|---|---|
| Operational ownership | Who manages authentication, persistence, routing, capacity and service operation? |
| Presence behavior | Which fields are ephemeral, how is disconnected state cleaned up, and how do cursor coordinates or selections stay meaningful as the document changes? |
| Traffic control | What is the default throttle, what range can be configured, how large are messages, when are updates published, and which clients receive them? |
| Capacity and failure handling | What is the simultaneous-connection limit per room, what do users see at the cap, and how do reconnects and high update rates behave? |
| Trust boundary | Where are identity authentication and authorization enforced, independent of presence-state ordering? |
How to test the capacity that matters for your editor
A useful capacity result must describe a workload, not just a participant count. Test representative room sizes and the actual awareness payload and publication behavior, then observe both server-side and client-side outcomes. Include reconnect behavior and geographical latency: a room that works under steady connections may behave differently when many clients reconnect or participants are far from the service.
- Measure delivery latency and update loss or staleness as participants and publishers increase.
- Track CPU, memory and network usage on the service, alongside rendering responsiveness on client devices.
- Test the real subscription scope; a room-wide broadcast and a filtered subscription pattern do not deliver to the same set of recipients.
- Exercise disconnects, reconnects and the configured stale-state behavior, and check whether departed users disappear as expected.
- Record the tested room size, update rate, payload shape, recipient scope, geography and observed degradation point. Do not present the result as a general limit beyond that workload.
Presence is not an identity or authorization mechanism
The Yjs awareness protocol does not authenticate awareness payloads. Its clock ordering resolves which state is newer; it does not prove that a participant is entitled to claim a particular identity or presence state. The Yjs y-protocols specification explicitly warns that a malicious peer can claim arbitrary cursor or presence data. Authenticate connections and enforce authorization in the application or provider trust boundary rather than trusting user identity fields supplied in awareness state.
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