How to Build a Real-time Chat App with PHP

Real-time chat is a ubiquitous feature in modern apps — from customer support widgets to collaborative team tools and social messaging. Building a reliable, scalable real-time chat app involves more than sending messages back and forth: you must handle presence, delivery guarantees, offline storage, typing indicators, security, and scaling. PHP is often associated with request/response web applications, but with modern tools and architectures it’s fully capable of powering real-time systems.

This guide walks through the conceptual design and operational decisions you'll face when building a production-ready chat app with PHP. No code — only patterns, trade-offs, and best practices.

Core requirements of a real-time chat app

Before choosing technologies, define what your app must support:

• Low latency messaging (near instantaneous)

• Message persistence (history, search)

• Presence & typing indicators

• Delivery guarantees (at-least-once, exactly-once considerations)

• Offline support (queue messages, sync on reconnect)

• Authentication & authorization

• Moderation & abuse controls

• Scalability and observability

Having clear functional and nonfunctional requirements helps pick the right transport and architecture.

Real-time transport options (pros & cons)

WebSockets (recommended)

WebSockets provide full-duplex communication ideal for chat. In PHP, common approaches:

• Long-running PHP servers like Swoole (high performance, native coroutines)

• Ratchet (pure PHP WebSocket library)

• Proxying WebSocket connections to other services (e.g., Node, Elixir) while PHP handles business logic

Pros: Low latency, bidirectional, push notifications from server.
Cons: Requires process management and different hosting model than typical PHP-FPM.

Server-Sent Events (SSE)

Unidirectional stream from server to client. Simpler but not suitable for client-initiated messages without fallback.

Pros: Simpler than WebSockets, good for notifications.
Cons: Not bidirectional (client still needs HTTP POST to send).

Polling / Long Polling

Works everywhere but wastes resources and increases latency.

Pros: Simple to implement on standard hosting.
Cons: Inefficient, poor scalability for many concurrent users.

Managed Real-time Services (Pusher, Ably, Firebase)

Outsource real-time transport and scale concerns.

Pros: Fast to build, robust scaling, SDKs for clients.
Cons: Vendor cost, reliance on external provider, possible privacy concerns.

High-level architecture

A common, production architecture splits responsibilities:

1. Frontend clients (web, mobile) — connect via WebSocket or service SDK.

2. API / Auth server (PHP) — manages user sessions, authorization, and stores messages.

3. Real-time server / broker — WebSocket server (Swoole/Ratchet) or managed provider that pushes events to clients.

4. Message store — database for persistence (SQL, NoSQL, or hybrid).

5. Message broker/queue — Redis Pub/Sub, Kafka, or RabbitMQ to decouple producers and real-time delivery.

6. Worker processes — background jobs for moderation, push notifications, analytics.

7. CDN / Push providers — for offline push notifications (APNs, FCM).

This separation lets PHP handle authentication and business rules while a suitable real-time layer focuses on connections and low-latency delivery.

Message persistence & storage patterns

Decide how long and where to store messages:

• Relational DB (MySQL/Postgres): Strong consistency, easy queries (search by conversation, full-text indexes). Great for structured metadata.

• NoSQL (MongoDB, DynamoDB): Flexible schema for varied message payloads and high write throughput.

• Hybrid: Store recent messages in Redis for fast retrieval and snapshot to durable storage for history.

Design tips:

• Keep message documents small (store attachments separately).

• Index by conversation_id and timestamp.

• Store delivery/read receipts as separate records for scalability.

• Use pagination (cursor or timestamp) to load message history incrementally.

Presence, typing, and read receipts

These real-time signals are ephemeral and should not burden your durable store.

• Presence & typing: Use in-memory stores like Redis with TTL keys. Clients set a key like presence:user:123 and update it periodically.

• Read receipts: Emit real-time events and persist the latest read cursor per user+conversation for auditability.

• Delivery semantics: Implement optimistic UI on clients and confirm with server acknowledgements.

Authentication & authorization

Security is critical for chat systems.

• Authenticate with JWT or session tokens and validate tokens when establishing WebSocket connections.

• Per-channel access control: The real-time server must check whether a user can subscribe to a channel or conversation.

• Token rotation: Issue short-lived WebSocket tokens that are renewed via API to minimize risk if a token leaks.

• Rate limiting & throttling: Limit message rates per user to prevent abuse.

Offline handling & sync

Users go offline — handle message delivery and state reconciliation:

• Store outgoing messages on server: If recipient is offline, persist and deliver when they reconnect.

• Message queues: Use durable queues (Redis streams or Kafka) to ensure messages aren't lost under load.

• Conflict resolution: Use timestamps + server-side monotonic counters for ordering; sync clients on reconnect by fetching messages after the last known cursor.

Moderation, compliance & content safety

Plan for content control:

• Automated filters: Run profanity and malware checks in worker processes.

• Human moderation: Queue questionable messages for review. Flagging should be quick and reversible.

• Retention policies: Enforce GDPR/CCPA requirements (right to delete) via data erasure workflows.

• Audit logging: Keep webhook logs and admin actions safe and searchable.

Scaling strategies

Real-time chat can be resource intensive. Key approaches:

• Horizontal scaling for real-time servers: Use a Pub/Sub layer (Redis, Kafka) so any WebSocket server instance can receive events for connected clients.

• Stateless API servers: Keep business logic stateless so you can auto-scale API fleet.

• Sharding: Partition users/conversations across Redis/Kafka topics to distribute load.

• Autoscale workers: Monitor queue lengths and spin workers up/down based on backlog.

• CDN & edge caching: Cache non-sensitive content like avatar images and static assets.

Monitoring & observability

Proactively monitor:

• Connection counts per node

• Message throughput and latencies

• Queue lengths and retry rates

• Error rates and unusual user behavior

Use distributed tracing, structured logs, and metrics dashboards (Prometheus + Grafana) to detect and act on issues early.

Mobile considerations & push notifications

Mobile apps may not keep socket connections alive. Use push notifications for:

• New messages while app is backgrounded (APNs for iOS, FCM for Android).

• Lightweight notifications that open conversation context and fetch message history.

Avoid sending full message bodies in push; fetch securely after user taps the notification.

UX considerations

A great chat app feels snappy and intuitive:

• Show local echo of messages immediately, then reconcile delivery status.

• Load recent history and then older messages lazily.

• Show presence + typing indicators for better conversational cues.

• Implement message edit & delete features with clear audit trails.

• Provide attachment previews, link unfurling, and inline images with progressive loading.

Security checklist

• Use TLS for all client-server connections.

• Validate all inputs server-side and sanitize stored content.

• Verify webhook signatures and implement idempotency on webhook processing.

• Store minimal PII and encrypt sensitive data at rest where needed.

• Enforce least privilege for internal services and rotate service credentials.

Conclusion

Building a real-time chat app with PHP is entirely feasible and practical when you separate concerns: PHP handles authentication, API logic, and persistence while a real-time layer (self-hosted or managed) handles connections and low-latency delivery. Use a message broker to decouple components, persist messages durably, and use in-memory stores for ephemeral state like presence. Prioritize security, monitoring, and scaling strategies early — they make the difference between a prototype and a production-grade chat service.