Databutton + Real-time App

Built a real-time app with Databutton?
We'll make it production-ready.

Real-time apps — chat, live collaboration, multiplayer features, live dashboards — have fundamentally different technical requirements than standard request-response web apps. Users expect sub-second updates, offline handling, and reliable message delivery. AI tools can set up a basic WebSocket connection, but production real-time features need connection management, message ordering, conflict resolution, and infrastructure that scales with concurrent users.

PythonReactFastAPIPostgreSQLStreamlit

Real-time App challenges in Databutton apps

Building a real-time app with Databutton is a great start — but these challenges need attention before launch.

Connection management and reconnection

WebSocket connections drop constantly — network switches, phone sleep, server deploys. AI tools open a connection but don't handle disconnection, reconnection, or missed messages during downtime. Users see stale data or lose messages without knowing it.

Message ordering and delivery guarantees

Messages must arrive in order and must not be lost. Network issues can deliver messages out of sequence or duplicate them. AI-generated real-time code has no message ordering, no deduplication, and no delivery confirmation — which means lost messages and confused users.

Conflict resolution in collaborative editing

When two users edit the same content simultaneously, whose changes win? AI tools implement 'last write wins,' which silently discards one user's work. Production collaboration needs operational transforms or CRDTs to merge concurrent edits correctly.

Scaling concurrent connections

Each WebSocket connection holds server resources. A single server can handle hundreds of connections, but thousands require load balancing with sticky sessions, a pub/sub layer (like Redis), and horizontal scaling. AI tools don't implement any of this.

Presence and typing indicators

Showing who's online, who's typing, and who's viewing a document requires frequent presence updates that can overwhelm your server. These updates need throttling, batching, and efficient broadcast — details AI tools skip entirely.

Message persistence and history

Real-time messages need to be stored for later retrieval — chat history, edit history, activity logs. AI tools send messages through WebSockets but don't persist them, so refreshing the page loses the entire conversation.

Security in real-time channels

Every WebSocket message needs authentication and authorization. Who can send messages to this channel? Who can read them? AI tools often create open WebSocket endpoints where anyone can listen to or inject messages into any conversation.

What we check in your Databutton real-time app

Connection lifecycle — reconnection logic, heartbeat, graceful degradation
Message delivery — ordering guarantees, deduplication, acknowledgments
Authentication — WebSocket connections verified, channel-level authorization
Scaling — connection pooling, pub/sub architecture, horizontal scaling readiness
Presence system — efficient online/typing indicators with throttling
Message persistence — chat history, search, pagination of historical messages
Conflict resolution — handling simultaneous edits without data loss
Offline support — message queuing, sync on reconnect
Performance — latency under 100ms for message delivery
Monitoring — connection counts, message throughput, error tracking

Common Databutton issues we fix

Beyond real-time app-specific issues, these are Databutton patterns we commonly fix.

highSecurity

SQL injection in AI-generated query strings

Databutton's generated FastAPI endpoints sometimes build SQL queries using f-strings or string concatenation with user-supplied parameters, bypassing parameterized query protections entirely.

highSecurity

No authentication on data API endpoints

Data pipeline endpoints are frequently generated without authentication middleware, exposing raw database access and sensitive business metrics to anyone who discovers the API URL.

mediumBugs

Unhandled data type mismatches crashing pipelines

Generated data processing code assumes clean input schemas. When upstream data contains nulls, type changes, or unexpected formats, pipelines throw unhandled exceptions and fail silently.

mediumBugs

Missing pagination on large dataset queries

Data queries load entire tables into memory without limit or offset clauses. With more than a few thousand rows, responses time out and memory usage spikes.

Start with a self-serve audit

Get a professional review of your Databutton real-time app at a fixed price.

External Security Scan

Black-box review of your public-facing app. No code access needed.

$19
  • OWASP Top 10 vulnerability check
  • SSL/TLS configuration analysis
  • Security header assessment
  • Expert review within 24h
Get Started

Code Audit

In-depth review of your source code for security, quality, and best practices.

$19
  • Security vulnerability analysis
  • Code quality review
  • Dependency audit
  • Architecture review
  • Expert + AI code analysis
Get Started
Best Value

Complete Bundle

Both scans in one package with cross-referenced findings.

$29$38
  • Everything in both products
  • Cross-referenced findings
  • Unified action plan
Get Started

100% credited toward any paid service. Start with an audit, then let us fix what we find.

Frequently asked questions

Can I build a real-time app with Databutton?

Databutton is a great starting point for a real-time app. It handles the initial scaffolding well, but real-time apps have specific requirements — connection management and reconnection and message ordering and delivery guarantees — that need professional attention before launch.

What issues does Databutton leave in real-time apps?

Common issues include: sql injection in ai-generated query strings, no authentication on data api endpoints, unhandled data type mismatches crashing pipelines. For a real-time app specifically, these issues are compounded by the need for connection management and reconnection.

How do I make my Databutton real-time app production-ready?

Start with our code audit ($19) to get a clear picture of what needs fixing. For most Databutton-built real-time apps, the critical path is: security review, then fixing core flow reliability, then deployment. We provide a fixed quote after the audit.

How much does it cost to fix a Databutton-built real-time app?

Our code audit is $19 and gives you a complete report of issues. Fixes start at $199 with our Fix & Ship plan. For larger real-time app projects, we provide a custom fixed quote after the audit — no hourly billing.

Get your Databutton real-time app production-ready

Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.

Tell Us About Your App