Overview
This comparison covers how servers handle client context across requests: a stateless server treats every request as self-contained with no memory of what came before, while a stateful server keeps track of session data tied to a specific client across multiple requests. The choice shapes how easily a system scales, recovers from failure, and routes traffic under load.
Comparison Diagram
Comparison Table
| Aspect | Stateless | Stateful |
|---|---|---|
| Request self-sufficiency | Each request carries all data needed to process it, independent of prior requests | Each request depends on context accumulated from prior requests in the same session |
| State storage location | Held externally (client token, database, cache) or not persisted at all | Held in server memory or local storage tied to a specific server instance |
| Load balancing | Any available server can handle any request; simple round-robin routing | Requests must be routed to the specific server holding the session (sticky sessions) |
| Horizontal scaling | Add or remove server instances freely with no coordination needed | Requires state replication or migration before instances can be added or removed |
| Failure recovery | A crashed server loses nothing; the next request is simply retried elsewhere | A crashed server can drop the active session unless state was replicated |
| Resource footprint per server | Lower memory overhead since no per-client data is retained between requests | Higher memory/storage overhead from tracking active sessions |
| Typical examples | REST APIs, DNS lookups, serverless functions, CDN edge nodes | Database connections, WebSocket sessions, FTP, multiplayer game servers |
Key Differences
- Stateless servers require no session affinity; stateful servers need sticky routing to reach the same instance.
- State in stateless systems lives in external stores or the client; state in stateful systems lives in server memory.
- Stateless architectures scale horizontally with ease, while stateful ones need state replication to scale out.
- A crashed stateless server loses nothing, but a crashed stateful server can drop an active session.
When to Use Each
Stateless
- Public REST APIs: Decoupling servers from client identity lets any instance handle any request, simplifying horizontal scaling.
- Auto-scaling microservices: Instances can be spun up or torn down freely without needing to preserve or migrate in-memory state.
- CDN and edge functions: Any edge node can serve a request without needing shared context from a prior request.
Stateful
- Real-time multiplayer games: Low-latency in-memory state per player session is essential and can’t be re-fetched on every tick.
- Database transactions: A transaction requires a continuous connection and context that must persist across multiple operations.
- Interactive terminal sessions: SSH or REPL sessions depend on maintaining command history and environment state across the connection.