For a real-time web chat app with authentication, user roles, and persistent data, here’s how Redis and PostgreSQL compare — and what I’d recommend:
🔧 Use Case Breakdown

Your app has:

    Real-time chat (low-latency message delivery)

    Users and roles (persistent relational data)

    Authentication (secure, durable, auditable)

    Likely needs message history, analytics, etc.

⚖️ Redis vs PostgreSQL
Feature	Redis	PostgreSQL
Real-time performance	⚡ Very fast (in-memory)	Fast, but slower than Redis for pub/sub
Data persistence	Optional (via RDB/AOF), not ideal for long-term	✅ Durable, transactional
Data modeling	Key-value / NoSQL, limited schema	✅ Full SQL, relationships, constraints
Pub/Sub support	✅ Native pub/sub for real-time messaging	❌ Not built-in (would need triggers + external tools)
Authentication, roles	Manual implementation	✅ Built-in, role-based permissions
Horizontal scaling	Complex, needs Redis Cluster	Easier with read replicas, sharding options
Best used for	Caching, queues, ephemeral messages	Business logic, user data, history, analytics
🏆 Recommendation: Use Both

For most production-grade real-time chat apps, the winning combo is:
✅ PostgreSQL for core data:

    Store users, roles, permissions

    Store chat rooms, messages (for history)

    Handle auth, tokens, metadata

    ACID compliance for data safety

✅ Redis for real-time layer:

    Use Redis Pub/Sub or Redis Streams to push messages instantly between clients

    Cache hot data (e.g., user presence, recent messages)

    Optionally use Redis for rate-limiting, session storage, etc.

🧱 Tech Stack Suggestion:

    PostgreSQL (via Prisma/TypeORM/Knex etc.)

    Redis (for pub/sub and presence)

    WebSockets or Socket.IO (for real-time messaging)

    JWT / OAuth2 (for authentication)

    Optional: Redis Streams if you want message persistence but not in the main DB

⚠️ Don't use Redis alone unless:

    You’re okay with ephemeral data

    You’re building a temporary or stateless chat (e.g. anonymous live chat)

    You don't need strong data consistency or rich querying