Migrate MongoDB to MongoDB
Certified — live-tested pathSame-engine MongoDB migrations are how you move between hosts, clouds, or versions — and they still fail in the boring ways: half-copied tables, stale sequences, missing indexes. DBShifts moves the schema and every row, defers constraints for speed, reseeds counters, and proves the result with row counts and 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 → MongoDB
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.
Frequently asked questions
Is MongoDB to MongoDB migration production-ready in DBShifts?
Yes — MongoDB to MongoDB is a certified pair. It passed DBShifts's live certification suite (schema conversion, data transfer, row counts, type-aware checksums over an edge-case fixture) and is battle-tested in production use.
How does DBShifts verify the MongoDB to MongoDB 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 MongoDB 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 MongoDB 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 MongoDB?
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 changes in a same-engine MongoDB migration?
Structurally nothing changes — types map one-to-one. The risks are operational: half-copied tables, sequences left pointing at 1, and indexes that never got rebuilt. DBShifts reseeds counters to MAX(id)+1, defers then rebuilds constraints and indexes, and proves the copy with row counts and checksums.
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