Migrate MongoDB to PostgreSQL
Beta — live-tested pathMigrating from MongoDB (the leading document database) to PostgreSQL (the most advanced open-source relational database) means every table, column type, key, index and row has to survive two engines' different opinions about data. This is a cross-model migration — documents become relational rows with an inferred schema — and the conversion rules are explicit, not guessed. DBShifts converts the schema with deterministic rules, transfers data in parallel batches, and validates the result with per-table row counts and type-aware checksums.
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How the migration works
Connect
Point DBShifts at your source and target. Credentials stay encrypted; SSH tunnels supported for private databases.
Analyze
Automatic schema introspection produces a migration plan: what converts automatically, what migrates with warnings, what needs human review.
Migrate
Schema is created on the target, data transfers in parallel batches with constraints deferred, indexes rebuilt after load.
Validate
Per-table row counts, type-aware checksums on both sides, FK integrity — plus a fidelity report listing anything lossy.
What DBShifts handles for MongoDB → PostgreSQL
Engine-specific rules baked into the conversion and transfer pipeline — verified by live certification of this exact pair.
- Schema is inferred by sampling documents — null values don't poison type inference (a nullable int stays an int column).
- Decimal128 maps to exact DECIMAL on SQL targets, never a float round-trip.
- Nested documents and arrays land as JSON/JSONB columns with data preserved byte-for-byte.
- _id becomes the primary key; ObjectId converts to its 24-character hex form.
- Bulk loads use sequence reseeding (setval to MAX) so SERIAL columns keep working after migration.
- ENUMs from MySQL become native CREATE TYPE … AS ENUM — validation semantics preserved.
- Foreign keys and indexes are applied after data load for dramatically faster transfers.
Frequently asked questions
Is MongoDB to PostgreSQL migration production-ready in DBShifts?
MongoDB to PostgreSQL is a live-verified beta pair: it passed the same certification suite as every other pair — a real migration with edge-case data validated by row counts and checksums — and ships with a post-migration fidelity report you can audit before cutover.
How does DBShifts verify the MongoDB to PostgreSQL migration was correct?
Three layers: per-table row counts on both sides, an order-independent type-aware checksum of row data (canonicalized so engine representation differences don't false-alarm), and FK integrity checks on the target. Rows that fail to insert are quarantined with the exact error — never silently dropped — and can be fixed and retried from the UI.
What happens to MongoDB types that PostgreSQL doesn't have?
They convert by deterministic rules with a recorded decision: a native equivalent where one exists, a portable fallback (TEXT/JSON/DECIMAL) where one doesn't. Every lossy conversion appears in the migration plan before you run and in the fidelity report after. You can override any mapping per column.
Can I keep MongoDB and PostgreSQL in sync after the initial migration?
Yes. DBShifts supports incremental sync (UPSERT-based delta transfers on a sync key) and, for supported sources, real-time change data capture so the target stays current until you cut over.
Do I need to write any SQL or scripts for MongoDB to PostgreSQL?
No. Connect both databases, review the generated migration plan (what's automatic, what migrates with warnings, what needs manual review — typically triggers and stored procedures), and run. Procedural code is transpiled best-effort and queued for human review rather than auto-applied.
What's the hardest part of moving MongoDB to PostgreSQL?
The data model itself differs (nosql → sql), so a relational schema is inferred from documents and nested data lands as JSON columns. DBShifts surfaces every inference and lossy conversion in the migration plan before you run, so nothing is guessed silently.
Go deeper
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