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Match the delivery model to what a presence event means
Presence signals often describe a changing condition: a player connected, moved to another server, or stopped responding. If a newer update makes an older one irrelevant, transient pub/sub can be a good fit for distributing changes to connected game servers or WebSocket gateways. The application still needs a way to recover the current view when an update is missed.
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Some messages that appear to be presence events are not safely disposable. A match result, purchase, or entitlement change may require reliable processing, retry, or an audit trail. Treat those as durable business events rather than relying on the same delivery policy used for ephemeral online-status refreshes.
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| Option | Documented behavior | Presence fit | Main limitation |
|---|---|---|---|
| Redis Pub/Sub | Broadcasts to currently connected subscribers and provides at-most-once delivery; it does not keep history for offline subscribers. Redis documents presence signaling and WebSocket fan-out as use cases. Redis Pub/Sub documentation | Live, replaceable updates distributed to connected nodes. | Recover the current state separately after a disconnect or missed message. |
| Redis Streams | Retains ordered events and supports consumer groups, acknowledgments, and replay. Redis Streams documentation | Presence transitions or follow-on work that needs recovery or history. | Retention and durable processing require storage and configuration. |
| Core NATS | Delivers to connected interested subscribers, without storing messages for offline subscribers. Core NATS documentation | Service messaging when loss is acceptable or the application provides recovery. | Missed messages are not replayed; use JetStream or application-level recovery for durability. |
| NATS JetStream | Adds persistent streams, replay, consumers, acknowledgments, and redelivery; pull consumers allow controlled consumption. JetStream documentation | Downstream events that need recovery, replay, or independent worker pacing. | Persistence adds storage, compute, and configuration overhead compared with transient Core NATS. JetStream documentation |
AWS also publishes a multiplayer-game reference architecture using Redis Pub/Sub with WebSockets and presence services. It illustrates an architectural pattern, not a controlled performance comparison. AWS multiplayer-game reference architecture
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Decide what must happen when a consumer is offline
Ask whether a restarted gateway or worker needs every event published during its outage. If the answer is no because it can fetch a fresh snapshot, transient messaging may be sufficient. If it must process missed transitions or resume pending work, a retained stream is the more suitable category.
Recovery and current truth are separate concerns. A retained event log can help reconstruct changes, but a queue choice alone does not define the authoritative online-player view. Keep or derive that current state independently, and reconcile reconnecting clients and servers against it rather than assuming transient notifications were never lost.
Set ordering, fan-out, and flow-control boundaries
- Ordering: Specify whether order matters per player, room, shard, or across the entire stream. Do not assume a system-wide ordering guarantee; verify the exact broker configuration and topology you plan to use.
- Fan-out: Decide whether every interested gateway should receive each presence change or whether one worker in a group should claim each task. Broadcast and work-queue patterns solve different problems.
- Consumer pace: If consumers need to request work at a controlled rate or acknowledge processing, compare Redis Streams consumer groups and JetStream consumers. Set backlog handling so a slow consumer cannot silently undermine freshness or recovery.
- Retries and duplicates: Design handlers to be idempotent. Acknowledgment-based redelivery can cause an event to be processed again, and at-least-once delivery does not guarantee exactly-once effects in the application. JetStream delivery documentation
Choose retention and operating overhead deliberately
Durability is not free. Retained events need an explicit retention window, storage capacity, monitoring, and policies for acknowledgments, retries, and consumer backlogs. NATS describes JetStream as the higher-compute and higher-storage option compared with Core NATS. Redis positions Streams as an option for retained processing, including shorter retention periods. NATS JetStream documentation Redis Streams documentation
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Use this selection sequence
- Separate ephemeral presence from durable events. Identify which updates can be superseded and which represent work or outcomes that must be preserved.
- Define recovery. Decide whether a reconnecting consumer can rebuild from an authoritative snapshot or must receive events published while it was away.
- Set the routing scope. Choose stable player, room, and shard keys that match the fan-out and ordering boundaries your application needs.
- Configure failure behavior. For retained streams, define retention, acknowledgment timeouts, retry limits, duplicate handling, and backlog policy; for transient messaging, specify how the application reconciles missed updates.
- Test the real topology. Load-test with representative concurrent connections, publish rates, room sizes, regions, reconnect storms, and failure recovery. The available documentation does not establish a universal latency, throughput, or cost threshold for game presence.
What the evidence can—and cannot—say about performance
Redis, NATS, and AWS documentation establish capabilities and example architectures, not a like-for-like benchmark across Redis Pub/Sub, Redis Streams, Core NATS, and JetStream. There is no basis here to call one a universal latency, throughput, fan-out, or scale winner. Measure the specific deployment, version, region, and workload you intend to run.
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