Auto-detect & preserve custom partial indexes during migrations

Executive Summary

Many teams building with ORMs and schema-as-code face silent failures because migrations neglect or change custom partial indexes: queries regress, SLOs slip, and DBAs or backend engineers must scramble during production deploys. This problem is particularly acute in mid-market and enterprise stacks using PostgreSQL or MySQL with Prisma, Rails, or Django—roughly 2 million development teams globally, representing an $8.0B addressable market (2M teams × $4K ACV) that already pays for migration and safety tooling. You could build an automated detection and preservation engine that scans schema-as-code, migration SQL, and application code to identify custom partial indexes, synthesizes safe-preserve patches, and emits migration-safe diffs and CI checks; deliverables would include plugins for Prisma Migrate, ActiveRecord, and Alembic, shadow-db dry-runs, and a human-reviewable workflow with one-click apply/rollback and audit logs. The product should emphasize low-friction developer UX so teams retain DB-specific optimizations without reverting to manual SQL surgery. Timing is favorable: the market is estimated at $8.0B with a Market Score of 92/100 and Revenue Potential 88/100, because ORM-centric development, pervasive CI/ephemeral environments, and advances in AST/ML-based code understanding make it feasible to detect patterns that previously required human review. To stand out you would need to target >95% detection accuracy across common patterns, ship deep integrations with major ORMs and CI providers, and consider an open-source core plus enterprise features like policy enforcement and audit trails; the main challenges are supporting engine-specific syntax, handling edge-case logic without generating false positives that block deploys, and earning trust through transparent tests and reproducible proofs.