Data Migration
Every database. Every direction.
7 engines, 49 source → target combinations — each one live-tested with real data, row counts and type-aware checksums before it shipped. Pick your path.
What it does
Schema conversion
Types, keys, indexes and constraints translated automatically across engines — with data-loss warnings surfaced before you commit to anything.
Checksum-verified data transfer
Every row is transferred and proven, not just counted — type-aware checksums catch silent corruption a row-count match would miss.
Zero-downtime CDC
Capture the change-log before the snapshot, replay after — the source stays live and writable the entire time.
Guided cutover
Go-live as a staged flip: drain the change stream, verify every row matches, then switch. Abortable at any point before the flip.
Dry run + rollback
Preview the full schema diff before moving a single row, and roll back automatically if anything looks wrong mid-migration.
Masking during migration
Mask sensitive columns as data moves — production data lands in staging or a new environment already de-identified.
All 49 migration paths
From MySQL
to MongoDB
From MariaDB
From PostgreSQL
From SQL Server
From Oracle
From SQLite
Frequently asked questions
What is database migration and why is it hard to get right?
Database migration means moving schema and data from one database (or engine) to another without losing anything or breaking what depends on it. It's hard because types don't map 1:1 across engines, constraints and indexes need translating, and any downtime or data-loss window can break production. DBShifts automates schema conversion, transfers data with checksum verification, and supports zero-downtime cutover so nothing is lost or offline.
How do I migrate a database with zero downtime?
Start incremental sync (CDC) alongside the initial data transfer — it captures every change the source receives while the bulk copy runs. Once the target has caught up, run a guided cutover: it drains the remaining change-log, verifies every table matches by checksum, then flips traffic. The source stays fully writable the entire time, right up to the flip.
Will I lose data during a database migration?
Every row transferred is checksum-verified against the source, not just counted — a silently truncated or corrupted value gets caught, not missed. Failed rows are quarantined for review and retry rather than dropped, and you can dry-run the full schema diff before a single row moves.
Can I move data between different database engines, like MySQL to PostgreSQL?
Yes — 49 source-to-target combinations across MySQL, PostgreSQL, MariaDB, SQL Server, Oracle, SQLite and MongoDB, each live-tested with real data before shipping. Schema, types, keys and indexes convert automatically; anything that can't convert cleanly is flagged before migration, not discovered after.
What happens if a migration fails partway through?
Failed batches retry automatically with backoff; rows that still fail land in quarantine for inspection and manual retry instead of silently vanishing. You can resume from the last checkpoint rather than starting over, and roll back to the pre-migration state if needed.
Can I test a migration before running it on real data?
Dry run shows the full schema diff and every data-loss warning up front, with nothing written. You can also generate a small, masked, FK-intact copy of your data to migrate first as a rehearsal before touching production.
Don't see your exact setup?
Every pair above runs through the same pipeline — schema conversion, parallel transfer, validation, rollback. Connect and find out in minutes.