I synced Stripe payments directly into a Supabase PostgreSQL warehouse using Make.com. Real-time agency dashboards, zero enterprise BI tool costs.
If you need to log into Stripe to see your cash flow, you do not have operations. You have a guessing game. This is a common issue that CRM API workflow overhaul addresses for many businesses.
The Data Warehouse Architecture
A small Make.com pipeline pulls data from Stripe and centralizes it in PostgreSQL through Supabase. That is your entire data warehouse.
The architecture: Stripe webhook events flow into Make.com, which writes directly to your Supabase database. Your frontend queries PostgreSQL for everything. One source of truth, one screen. You can see real examples of this approach in our production case studies.
1. The ETL Pipeline
Build a webhook in Make.com that catches Stripe charge.succeeded and invoice.paid events. Use the Make.com PostgreSQL module to execute raw SQL INSERT statements into your Supabase tables.
INSERT INTO agency_revenue (client_id, amount, mrr_impact, created_at)
VALUES ({{1.customer}}, {{1.amount_captured}}, TRUE, NOW())
ON CONFLICT (client_id) DO UPDATE SET amount = agency_revenue.amount + EXCLUDED.amount;2. Real-Time Frontend
Connect Retool or a custom React app directly to Supabase. You get a fast dashboard that tracks MRR churn, client LTV, and daily cash flow. No SaaS bloat, no third-party dependency. For more complex needs, see our business AI agents.
Want the exact database schema? Download the Blueprint or AI Workflow Repair Intake. For a detailed comparison of automation platforms, see Zapier vs Make vs N8n for CRM automation.
What to sync
Stripe events worth capturing in Supabase: payment intents, subscriptions (created, updated, cancelled), invoices, refunds, and disputes. Everything else is noise that clutters your analytics tables.
The Make.com webhook receives the Stripe event, converts it to your Supabase schema, and upserts. Idempotency keys on every write prevent double-counting when Stripe retries webhooks. For the CRM side of the same pattern, see the speed-to-lead architecture.
The error handling that matters
Stripe webhooks fail silently if you do not watch for them. Every failed webhook needs a retry queue and an alert after the third failure. I log every event to a staging table first, then convert. That way a bad schema change does not destroy your production data.
| Operational layer | Fragile default | Production architecture |
|---|---|---|
| Trigger reliability | Polling zaps that miss bursts or hit rate limits | Signed webhook receiver with immediate queue persistence |
| Error handling | Scenario stops mid-run leaving partial records | Transactional steps with dead-letter queue and safe replay |
| Platform cost | Per-task billing that explodes with volume | Direct API or lightweight worker architecture with flat compute cost |
| Visibility | Thirty-step visual spaghetti nobody can debug | Documented data contract with correlation IDs across every step |
FAQ
How do I sync Stripe payments into Supabase?
Catch Stripe webhook events in Make.com and use the PostgreSQL module to run raw SQL inserts into your Supabase tables. Your frontend then queries PostgreSQL for everything.
Which Stripe events should I store in my warehouse?
Store payment intents, subscriptions as they are created, updated or cancelled, invoices, refunds and disputes. Everything else is noise that clutters the analytics tables.
How do I stop Stripe webhooks from double-counting?
Put idempotency keys on every write so Stripe's retries cannot create duplicate rows. Log each event to a staging table first and load it into production afterward, so a bad schema change does not destroy production data.
Can I build a real-time dashboard on Supabase without a BI tool?
Connect Retool or a custom React app directly to Supabase and you get a fast dashboard for MRR churn, client LTV and daily cash flow. That replaces enterprise BI tools with one PostgreSQL database.