Database schema & records
Schema mapped to Postgres, field types translated, every record migrated, and relationships preserved across the whole data model.
Database migration service
We migrate your database, user accounts, files, images, and Option Sets out of Bubble, then help you improve the new setup where it makes sense so it is ready for AI-powered development.
Disclaimer
Bubble is an incredible piece of technology, and we owe a lot to it. But times have changed - building with AI is now faster, more flexible, and often cheaper.
Audit, scope & mapping plan
In progressDatabase, Option Sets, user accounts, files, and privacy rules reviewed. You get a written mapping plan before any data moves.
Migrate to a test database
Schema, records, auth accounts, files, and security rules migrated into a separate Postgres database. Production is never touched first.
Validation & mock cutover
Counts, integrity, and references checked against the live Bubble source. Mock cutover rehearses the real one with incremental sync still running.
Live cutover & guided rollout
Final sync, then handoff. Rollout can move progressively — start with a smaller group, monitor, then move the rest.
Optional schema redesign
After parity is proven, restructure the parts of the schema that should not be carried over as-is — usually in a separate branch.
Database, auth, files, Option Sets, and the security model — together, with someone driving every decision and validating the result.
Schema mapped to Postgres, field types translated, every record migrated, and relationships preserved across the whole data model.
Bubble users moved into real Supabase Auth accounts, linked back to their records, with a clean first-login flow planned with you.
Bubble-hosted assets migrated to Supabase Storage with references rewritten so records keep pointing to the right files.
Option Sets turned into real relational tables your code can query and extend, instead of Bubble-only abstractions.
Bubble privacy rules mapped to Postgres row-level security — or redesigned with you if you want a cleaner, safer model.
Migrate to a test database first, validate against your live app, run a mock cutover, then move to live — no hard one-shot switch.
Process
Database, Option Sets, user accounts, files, and privacy rules reviewed. You get a written mapping plan before any data moves.
Schema, records, auth accounts, files, and security rules migrated into a separate Postgres database. Production is never touched first.
Counts, integrity, and references checked against the live Bubble source. Mock cutover rehearses the real one with incremental sync still running.
Final sync, then handoff. Rollout can move progressively — start with a smaller group, monitor, then move the rest.
After parity is proven, restructure the parts of the schema that should not be carried over as-is — usually in a separate branch.
Share your app details and get a migration roadmap, estimated timeline, and recommended rollout sequence.
Prefer to talk first? Book a call below.
More alternatives
FAQ
Quick answers to what people usually ask before getting started.
The full app migration rebuilds your whole product — frontend, backend, auth, data, and infrastructure. This service focuses on the backend and data layer: database, user accounts, files, Option Sets, and security. It is for teams that want help with the highest-risk parts of the move first, or only need that scope. The frontend stays on Bubble (or wherever you decide), and you can come back later for the full rebuild.
Same migration engine underneath. The service adds a real engineer driving it — a written audit, schema and Option Set decisions, auth and file migration handled together, validation against your live Bubble app, security model mapping, and cutover support. Pick this when the schema is complex, the cutover is tight, or your team doesn't want to own every backend decision alone.
Bubble users are moved into Supabase Auth and linked back to their records. The typical flow is a password reset on first login, which is easy to manage and communicate. We help you plan the first-login experience, how to message the change to users, how new signups should work in the new system, and what rollout sequence makes sense. Auth is one of the biggest sources of fear in a Bubble migration — it gets dedicated attention here.
In most cases, no perceptible downtime. The migration runs as an incremental sync, so Bubble keeps working while data lands in Postgres. Cutover can be staged — start with a smaller group, validate, then move the rest. Exact rollout details depend on things like domain configuration, integrations, and how login changes are handled.
Two options. Migration mode keeps the existing logic — your Bubble privacy rules are mapped into Postgres row-level security so access stays the same. Rethink mode redesigns the model where it makes sense, so it is safer and clearer in the new stack. Most teams pick a hybrid: keep what works, redesign what didn't.
Yes, but usually after the first migration is stable. The first goal is safe extraction — get everything into Postgres correctly. Then we can redesign parts of the schema in a separate branch: replace Bubble-shaped structures, restructure Option Sets, add proper join tables, clean up the data model. This keeps the initial cutover focused on parity and lets the redesign happen without putting the migration at risk.
Every Bubble-hosted image and file is migrated to Supabase Storage (or another target you prefer), and the references inside your records are rewritten so nothing breaks. People worry as much about broken file references and missing images as they do about missing rows — this is handled with the same care as the database itself.
Most engagements are 2–6 weeks from audit to live cutover, depending on schema size, Option Set complexity, how many users and files there are, and how strict the validation pass needs to be. The audit produces a concrete plan with dates, not an open-ended estimate.
Any Postgres-compatible target. Supabase is the default because it bundles auth, storage, and database, which keeps the stack simple. Neon, AWS RDS, Cloud SQL, or self-hosted Postgres also work — auth and storage can be wired to other providers if your team prefers.