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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesThere is no universal maximum number of people who can use collaborative cursors in one document. Capacity depends on how often clients publish presence updates, how large those updates are, how many peers receive them, and how the service distributes traffic. Protocol timers and hosted-plan caps are useful constraints, but neither is a general-purpose capacity benchmark.
What “fan-out” means for collaborative cursors
Fan-out is the distribution of one client’s update to the other clients that need to know about it. A cursor movement may be tiny, but a room-wide system can deliver that movement to many peers. As rooms grow or clients publish more often, the aggregate delivery work grows too.
A useful planning heuristic for an unfiltered room broadcast is:
active publishers × updates per second × recipients per update × average payload size
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This is architectural arithmetic, not a performance law or benchmark. It makes the variables visible; it does not predict a particular server’s capacity. Subscription scope, network conditions, implementation details, rendering work, and distribution topology all affect the result.
Three different boundaries are easy to confuse:
- Protocol behavior: how clients represent updates, decide which state is newer, and identify stale peers.
- Service limits: explicit restrictions imposed by a hosted product or plan.
- System capacity: the workload-specific point where latency, CPU, bandwidth, memory, or rendering quality becomes unacceptable.
A protocol’s timers and a vendor’s room cap answer different questions from “How many users can this editor support smoothly?”
Presence is temporary state, not saved document content
Collaborative editors usually need to share two kinds of information. Document edits are durable shared content: text, formatting, or other changes that should remain after a user disconnects. Presence is temporary awareness state: for example, a participant’s cursor, selection, avatar, typing indicator, or online status.
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Yjs Awareness is separate from the persisted Yjs document. Yjs documentation says, “Awareness information isn’t stored in the Yjs document, as it doesn’t need to be persisted across sessions.” Its protocol tracks per-client state using client IDs and increasing clocks; a newer clock replaces older known state, and a null state marks a client offline. These clocks order updates—they do not authenticate the identity or permissions claimed in an update.
Liveblocks describes Presence similarly as temporary JSON state that disappears when a connection ends. Its presence and cursor features provide a hosted implementation path for common interface state. In either model, a cursor is not itself a durable document edit.
Yjs timers are for liveness, not cursor animation
Yjs Awareness documentation describes a 30-second timeout after which a peer with no update is marked offline. The Yjs 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.
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Those are protocol liveness rules. They do not mean an editor should visibly move a cursor only once every 15 seconds. A product’s cursor responsiveness is a separate design decision: the interface may publish movement more frequently, while awareness refreshes also help maintain the peer’s online state.
Hosted room caps and message throttles are product settings
Liveblocks’ documented maximum simultaneous connections per room varies by plan. Its limits page, accessed October 5, 2026, lists:
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| Liveblocks plan | Maximum simultaneous connections per room |
|---|---|
| Free | 10 |
| Pro | 10 |
| Team | 50 |
| Enterprise | 100 |
These are Liveblocks plan limits, not estimates of what every editor architecture can support. Liveblocks’ capacity guidance says additional users cannot join once a room reaches its plan’s cap. Plan terms can change, so confirm the current limit with Liveblocks before relying on it.
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Liveblocks documents a default WebSocket message throttle of 100 milliseconds, configurable from 16 to 1,000 milliseconds. Its tutorial describes 16 milliseconds as approximately 60 frames per second. That is a setting range, not a universal recommendation: publishing more often can make motion appear smoother, but it also creates more outbound and downstream message work, and the client still has to render the resulting state.
How the implementation changes the capacity question
Self-managed Yjs provider
Yjs is a data framework, not a hosted room-capacity promise. The Yjs WebSocket provider uses a client-server model to distribute document updates and awareness among connected clients. The Yjs provider documentation notes that the same shared document may be handled by multiple servers; that is a topology consideration, not a published fan-out ceiling.
Self-hosting gives an engineering team operational control, along with responsibility for authentication, persistence, routing, capacity planning, and failure handling. The actual ceiling depends on the deployed provider and workload; the cited Yjs documentation does not establish a universal maximum room size.
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Hosted collaboration service
A hosted service can take on parts of synchronization and distribution, while exposing product-specific behavior such as connection caps and throttling settings. Liveblocks offers presence and cursor APIs and a Yjs integration that exposes Liveblocks Presence as Yjs awareness. The relevant comparison is therefore not just “self-hosted versus hosted”: it also includes operational ownership, limits, configuration, and how the service behaves when a room reaches a cap.
The published figures here do not provide an apples-to-apples performance benchmark between these approaches. Choose based on the requirements and workload you can actually validate, not a presumed ranking.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What to measure before setting a room limit
Define a target workload rather than selecting a participant count in isolation. Test with representative document activity, presence payloads, network conditions, and reconnect patterns. Record the point at which the experience no longer meets your own responsiveness and reliability requirements.
- Set a realistic room profile. Specify expected simultaneous participants, how many are actively moving a cursor, and whether every participant should receive every other participant’s state.
- Define the update pattern. Measure the publication rate and payload size for the presence states your editor actually sends. Include bursts, selection changes, and idle periods if they occur in normal use.
- Track both delivery and interface costs. Observe message volume, latency, CPU, memory, bandwidth, and rendering performance. A server can distribute messages successfully while a client struggles to draw many remote cursors.
- Exercise adverse conditions. Include reconnects and the geographical latency expected for your users. Check whether stale cursors disappear as intended and whether users get a clear response when a hosted room cap prevents joining.
- Change one traffic-control choice at a time. Test publication frequency, coalescing intermediate pointer positions, skipping unchanged or off-screen cursors, and limiting subscriptions to relevant scopes. These are options to measure, not guaranteed optimizations.
Keep presence traffic distinct from durable document updates in the design and in operational measurements. Otherwise it becomes harder to tell whether a performance problem comes from editing, awareness fan-out, or client rendering.
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The Yjs awareness protocol does not authenticate payloads: a malicious peer can claim arbitrary cursor or presence data. A clock resolves freshness ordering, not whether a client is entitled to assert a particular identity, role, or state. Authentication and authorization therefore belong at the application or provider boundary.
Also decide how cursor and selection state maps to document positions as content changes. Presence may be temporary, but users still need the displayed cursor to remain meaningful while edits arrive. The right representation and update behavior depend on the editor and collaboration stack; the cited sources do not establish one universal approach.
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