Data migration

Move data on supported warehouse and database paths.

The active runtime supports Redshift to BigQuery, MySQL to Cloud SQL, and MongoDB to Firestore. Each migration requires valid source access, destination access, an approved plan when the run raises a gate, and validation before cutover.

What this path delivers

3

Supported data paths

Approval-gated

Qualifying execution

Required

Validation step

Customer-owned

Generated assets

Before migration

Identify schema, query, and cutover differences before execution.

A source and destination can store similar data but use different schemas, data types, query behavior, indexes, and operational controls. Record these differences in the migration plan.

01

Schema differences

Source data types, keys, indexes, and constraints may not map directly to the destination.

02

Query differences

SQL dialects, aggregation behavior, and document queries can produce different results after migration.

03

Pipeline dependencies

Applications, reports, jobs, and credentials can depend on source-specific behavior.

04

Cutover risk

The team must define validation checks, rollback conditions, and ownership before cutover.

Migration sequence

Map the source, plan the conversion, and validate the destination.

Use the implemented template for the selected path. Review source dependencies and mappings before execution. Compare destination records and queries before cutover.

01

Discovery

Record the source, destination, schemas, dependencies, credentials, and cutover constraints.

02

Analysis

Identify incompatible data types, queries, indexes, constraints, and application dependencies.

03

Plan

Define mappings, transfer steps, validation checks, approval conditions, and recovery actions.

04

Execute

Run the approved migration steps and record status, messages, and tool activity.

05

Validate

Compare record counts, data values, schemas, and representative queries before cutover.

Owned deliverables

Keep the migration plan, generated assets, and validation record.

The exact deliverables depend on the supported path and approved scope. Generation does not replace source-owner, destination-owner, or production review.

Source and destination inventory
Schema and data-type mappings
Migration plan and approval context
Generated or migrated artifacts for the supported path
Run status and activity record
Record and query validation results

Validated migration package

You get the plan, the generated assets, the run record, and validation results for the selected source and destination.

Timeline

Scoped per system

Paths

Three implemented types

Cutover

Validation required

Active path registry

Supported data source and destination pairs.

A source or destination not listed here requires implementation and validation before MigrateForce can schedule it as supported work.

Amazon Redshift to Google BigQueryMySQL to Google Cloud SQLMongoDB to Google Firestore
Confirm path support

Name the source, destination, dependencies, and cutover requirements.

MigrateForce will confirm whether the path is implemented before discussing execution scope.

Three supported pathsApproval when requiredValidation before cutover