Start from the problem you have today
Migratrix is one platform, but teams arrive at it for different reasons. Pick the situation that sounds like yours and see the specific workflow that addresses it.
Common starting points
Oracle to PostgreSQL
Leaving Oracle for PostgreSQL. The hard part is designing the target model and proving the conversion is faithful before a one-time full load.
SQL Server to PostgreSQL
Both engines sit in the tested type-mapping matrix, with CDC available to shorten the cutover window.
MongoDB to MySQL
Turn nested documents into reviewed tables, or keep selected fields as JSON, then load with CDC if you need a short cutover.
Let Executors work without handing over production
Coding assistants and internal copilots keep ending up with more database access than anyone intended. Keep the speed, and keep a named person on the last step before a protected environment changes.
Prove control to an auditor
You need separation of duties, documented approvals, and an answer to "who changed production and who signed off" that is not a chat log.
Stop being surprised by drift
Staging does not match production, nobody knows when they diverged, and every release carries the risk of a missing column nobody noticed.
Take production credentials away
Too many engineers hold production passwords because support work requires reading real data. You want to remove the credentials without blocking the work.
Database CI/CD
SQL in GitHub or GitLab, then environment gates. Merge is not permission to run production. Not a Flyway or Liquibase runner.
Modernize the engine
Oracle, SQL Server, MongoDB, or a warehouse path. Conversion Studio models the target. Procedural code stays yours.
Relational to Snowflake
Warehouse types you review before anything runs, then a load with validation per entity.
What each team gets out of it
Platform and DevOps
Database changes stop being the one manual step in an otherwise automated pipeline. Promotion is modelled once and reused, and the Executor keeps data plane access inside your network.
DBAs and data platform owners
Review changes with dependency and risk context instead of reading raw SQL in a ticket, and stop being the bottleneck for every read-only question about production.
Application engineers
Ship schema changes without filing a ticket and waiting. Write the change, see the risk analysis, get approval, and watch it promote.
Security and compliance
Enforce separation of duties and least privilege on the database tier, with an audit trail that ties every change and every production read to a named person.