Bubble.io to Production SaaS Migration
Outgrew Bubble limits on users, performance, and integrations — migrated to custom code without losing live customers.
- Industry
- Startup
- Location
- Netherlands
- Timeline
- 14 weeks
By the numbers
- 8s → 1.5s
- Page load time after migration
- 800
- Users migrated with zero downtime
- 0
- Downtime on cutover
- ~5x
- Faster page loads
The problem
A startup validated product-market fit on Bubble.io and grew to 800 paying users faster than expected. Performance degraded — complex pages took 8+ seconds to load, workflow runs hit Bubble's limits mid-month, and a critical Stripe webhook integration broke under volume. The team could not add role-based permissions they needed for enterprise deals. Investors wanted a technical due-diligence path off no-code before the next raise.
What we built
We migrated the core product to a production-grade Next.js and Node.js stack — preserving user accounts, subscription data, and the primary user workflow. Bubble stayed live during migration; users were moved in cohorts with zero downtime cutover. The new codebase supports custom RBAC, reliable webhooks, and the performance headroom to scale past 10x current users.
Our approach
- Mapped every Bubble workflow, data type, and API connection to a migration spec
- Prioritized the one workflow that 90% of users depend on — migrated that first
- Built parallel system with Stripe subscription sync and user auth parity
- Ran dual-write period so Bubble and production stayed in sync during testing
- Migrated users in weekly cohorts with email comms and rollback plan
- Decommissioned Bubble after 30-day stability window on production
Results & outcomes
- Page load times dropped from 8s to under 1.5s on core workflows
- Zero customer churn during the 14-week migration
- Enterprise RBAC and custom permissions shipped post-migration
- Stripe webhooks reliable at 3x previous transaction volume
- Investor due diligence passed with owned codebase and deployment pipeline
8s → 1.5s page loads
Analysis
The trigger was a ceiling, not a preference: Bubble hit workflow limits at around 800 users — capped API calls, slowing pages, and custom logic that had become unmaintainable. The hard requirement was a zero-downtime cutover for a live user base, which shaped the whole approach: parallel run, data-parity checks, and a staged switch. The 8s→1.5s improvement matters less as a vanity number than as headroom — the production codebase scales past the point where the no-code tool simply stopped, so growth is no longer gated by the platform.