Data migration you can check, not just trust.
Scattered spreadsheets, an old database nobody understands, or exports from a tool you are leaving. Remqa's engineers move it into one place your team can query, and prove the numbers match.
Remqa moves data from spreadsheets, old databases and SaaS exports into Postgres, BigQuery, Snowflake or a new application database. Every table is reconciled with row counts, totals and relationship checks, and your team spot-checks real records before cutover.
- Cleaning rules are written down and approved before data moves
- Reconciliation uses plain queries you can rerun yourself
- Ongoing pipelines can be rebuilt after the move
- Targets include Postgres, MySQL, BigQuery, Snowflake, Redshift and Supabase
What we move
- Spreadsheets and exports: Excel, Google Sheets, CSV dumps and app exports turned into clean, typed tables
- Old databases: MySQL, SQL Server, Oracle, Access and legacy Postgres into a modern database or warehouse
- App data: data pulled out of SaaS tools you are leaving, through their APIs or exports
- Ongoing syncs: pipelines rebuilt so new data keeps flowing after the move
Where it goes
Postgres, MySQL, BigQuery, Snowflake, Redshift, Supabase, or the database behind your new application.
How a data migration runs
Map. Every object, field, owner, stage and file is mapped from old to new. You sign off on the map before anything moves.
Test run. A full trial migration into a sandbox or a copy of the new system, so problems show up before go-live, not after.
Verify. Record counts reconciled, relationships checked, and spot checks on real records with your team.
Cut over. A planned switch with a short freeze window, then a final delta sync for anything that changed during the test run.
Keep the old system read-only. Nothing is deleted until you are happy with the new one.
How we verify
Every table gets reconciled: row counts, sums of key numeric columns, distinct counts on IDs, and checks that relationships still join. Your team then spot-checks real records they know well. You get a short report showing what matched, what was cleaned and what was deliberately left out.
Where AI helps
AI is useful for profiling messy data, suggesting column types and mappings, normalising free-text values and writing transform code. Engineers review the logic, and reconciliation is done with plain queries, so the result is something you can check yourself.
Moving a CRM or recruiting database? See CRM migration and ATS migration.
Common questions.
How do we know nothing was lost?
We reconcile every table with row counts, totals on key columns and relationship checks, and share the results. Your team also spot-checks records before sign-off.
Can you clean the data during the migration?
Yes. Deduplication, type fixes and value normalisation are part of the mapping, and every cleaning rule is written down for you to approve.
Do you build ongoing pipelines too?
Yes. If data needs to keep flowing after the move, we rebuild the sync or pipeline and hand over the docs.
Where should our data end up?
It depends on how you use it. Postgres suits apps and moderate reporting, while BigQuery or Snowflake suit heavier analytics. We recommend one in the first call.
Tell us what you are moving.
In 30 minutes we look at your current system, where you want to go and what could go wrong. You leave with a plan, whether or not you work with us.
Book a free migration call