以下の詳しいガイドと説明用の事例は英語です。例に含まれる業務データは架空のものです。
Where MongoDB fits
Document-shaped records whose structures vary for a useful business reason.
When to choose another approach
Flexible structure still needs validation and a migration policy. Highly connected financial rules may be simpler in a relational model.
Worked example and evidence
Fictional catalogue: cameras have lens fields and furniture has dimensions. Add a category while keeping old records readable and validating each agreed shape.
What you need to supply
Document examples, query patterns, relationships, version history and growth assumptions.
What acceptance should demonstrate
Read old/new shapes, reject invalid documents and measure representative queries with the intended indexes.
Running costs and responsibilities
Budget schema evolution, indexes, hosting, backups and data repair. Assign a model owner.
Technical scope to confirm
Flexible documents are a modelling choice, not a guarantee of automatic scale or no schema work.
A proposal should identify the systems and data, direction of sync, access feasibility, failure handling, named owners and included deliverables. Listing this technology does not imply a prebuilt connector, vendor partnership or included feature.
What does schema evolution cost to maintain?
Allow for validation updates, backfilling records, index changes and maintaining readers during rollout. Estimate from the actual record shapes and consumers.