Fivetran vs DBShifts
Fivetran is a managed ELT platform. It syncs data from operational databases and SaaS applications into an analytics warehouse on a schedule, keeping connectors and schema drift handled for you.
When Fivetran is the better choice
Stated first, because it is often true and you will find out either way.
- ✓You are building analytics and want operational data continuously landed in a warehouse.
- ✓You need a long tail of SaaS connectors — Salesforce, Stripe, HubSpot — not just databases.
- ✓You want the pipeline itself to be someone else's operational problem.
Where DBShifts is different
Differences, not a scorecard.
These solve different problems
Fivetran replicates into a warehouse for analysis; the source stays authoritative. DBShifts is for the case where the target BECOMES authoritative — you are leaving the old database, so the schema must convert, every row must be proven, and you need a rollback if it goes wrong.
Schema conversion, not schema mapping
ELT normalises source data into warehouse tables. Migration requires converting types, constraints, indexes, foreign keys and identity columns into a different engine's dialect so the target can serve production traffic.
Cutover and rollback
A pipeline has no concept of go-live. DBShifts provides a staged cutover that drains the change stream, verifies, then switches — abortable until the last moment — plus one-click rollback.
Governance over the source, not only the destination
DBShifts governs access to the operational database itself: masked browsing, unmask grants, access reviews, and scoped tokens for AI agents.
Questions people ask about Fivetran
Can I use Fivetran to migrate a database?
You can move the data, but migration needs more than movement: the schema has to convert into the target dialect, constraints and foreign keys have to survive, and you need to prove every row landed before you cut traffic over. Fivetran is built to land data in a warehouse for analysis, where the source stays authoritative.
What is the difference between ELT and database migration?
ELT keeps an ongoing copy somewhere useful for querying; the original system remains in charge. Migration ends with the target BECOMING the system of record, which is why it needs schema conversion, row-level verification and a rollback plan that ELT has no reason to provide.
Does Fivetran handle cutover?
Cutover is not part of what a pipeline does — there is no moment where it stops writing to the old system and starts serving from the new one. DBShifts provides that as an explicit staged step: drain the change stream, verify, switch, with the option to abort until the final moment.
Try it against your own schema.
Connect a database read-only and DBShifts reports every lossy conversion before anything moves. Free tier, no card.