Moving data between systems without losing any of it.

I have migrated ten million records out of MongoDB using Python sanitization and chunked batches, verified by count at every stage, with zero loss. The platform that data belongs to has since reunited over 140,000 pets with their families, which is the part that would have made losing records unforgivable.

A migration is where you find out what a system actually believes about its own data. The nulls nobody expected. The duplicates two teams created independently. The field that quietly changed meaning in 2021 and nobody wrote down.

You cannot fake your way through one. Either every record lands or it does not, and that binary is rare in software. Most of the work is in the audit before anything moves, not in the moving.

Audit the source first and write down what is actually in there, including the ugly parts. Map old shape to new shape and agree it with you. Write sanitization that handles the edge cases the audit found. Move in staged batches with verification at each stage rather than one overnight run. Keep a rollback path open the whole way.

MongoDB, PostgreSQL, MySQL, Xano, Supabase, Airtable, and most things with an API. Also platform migrations: Bubble, Adalo or Webflow to custom code.