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What expand-and-contract means
A direct schema change can make one application version incompatible with the database or another version still running during deployment. Expand-and-contract replaces that single breaking change with intermediate states designed to support overlapping releases.
The pattern is commonly described as three phases: expand, migrate, and contract. OpenStack Glance’s contributor guidance says its expand migrations “MUST be additive in nature”: the new schema is added without removing what old services still need. Its separate migrate phase moves existing data, and its contract phase performs incompatible cleanup. Those are Glance’s project-specific migration rules, not a universal mandate for every tool.
Prisma’s guide illustrates the same idea by replacing a published boolean with a status enum: add the new field, backfill it, move application behavior to it, and eventually remove the boolean. The exact number of releases, transaction boundaries, and deployment steps depends on the application and migration system.
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Example: safely renaming a column
Suppose an application uses orders.status, and the intended name is orders.order_status. Renaming or dropping the old column immediately can break an application instance, job, or report that still expects status. Instead, keep both columns available during the transition.
- Expand: add
order_statuswhile leavingstatusintact. - Keep writes current: if writes can continue during the transition, ensure new and old representations stay synchronized. Dual-writing in application code is one option; a database trigger or a migration tool’s supported mechanism may be another.
- Backfill: populate
order_statusfor existing rows fromstatus. - Move reads: deploy application code that reads the new column, then confirm remaining application versions and other consumers no longer depend on the old one.
- Contract: remove
statusand any temporary synchronization mechanism after the compatibility and data checks pass.
A PGDay UK 2025 presentation by Andrew Farries, Staff Software Engineer at Xata, depicts this operational overlap: add a field, run a version that writes both representations, wait for rollout, backfill, move reads, and drop the old field after the later rollout completes. The talk also identifies pgroll as an open-source PostgreSQL migration tool; it is an example, not an independent evaluation of the tool.
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How to plan and run the migration
1. Define compatibility before changing the schema
List the application versions and every other consumer that may use the affected data: scheduled jobs, reports, scripts, integrations, and prepared queries. Establish whether old and new code can both work with the expanded schema. Decide how writes will remain correct while existing rows are migrated, and define the checks that will demonstrate the new representation is valid.
2. Expand without removing what old code needs
Add the new field, table, or other structure while retaining the old one. For Glance, expand migrations must be additive and usable while old services run. Document temporary triggers or other synchronization behavior so the team knows when it is safe to remove them.
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3. Migrate existing data and keep ongoing writes correct
Backfill historical rows with a process suited to the table size and workload. Make the work observable and safe to resume or repeat where the transformation allows it. If writes can occur during the backfill, keep both representations synchronized so later writes do not leave the new field stale.
Keep schema changes and data-only work separate when the chosen migration workflow calls for it. Glance, for example, specifies that its data migration phase should not perform schema changes. There is no universal batch size or throttle: workload, database behavior, and recovery requirements determine those choices.
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4. Shift reads only after checking the new data
Deploy code that reads the new representation, and verify that transformed values meet the application’s correctness conditions. In Prisma’s example, the new status value is checked against the prior published boolean before application behavior is moved over. Also confirm that old application instances and other consumers have completed their transition.
5. Contract after old dependencies are gone
Remove the old column, table, or temporary synchronization mechanism only when no relevant code still depends on it and the required data checks have passed. Contract is deliberately delayed because it makes the intermediate state compatible; removing the old shape too early recreates the original breaking change.
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What the pattern does—and does not—protect against
Expand-and-contract manages compatibility risk between schema states and application versions. It does not by itself prevent locks, long-running DDL, replication lag, excessive migration load, faulty transformations, or missed consumers. Whether a particular DDL operation blocks writes depends on the database engine, version, operation, workload, and deployment method. Check the exact engine- and version-specific behavior before relying on a migration being nonblocking; the general sequencing pattern is not proof of zero downtime.
Compared with a single breaking migration, the staged approach trades a simpler one-step change for more intermediate states and coordination. Before choosing it, consider whether mixed application versions can use the intermediate schema, whether data can be synchronized and backfilled reliably, how much operational load the work creates, what the specific DDL does, and how recovery works after each phase. For a simple additive field that existing code does not require, a full transition may be unnecessary. Renames, representation changes, and removals are stronger candidates for retaining both shapes during migration.
Rollback and recovery
Before contract, the old field or structure may still be available, which can leave more options for reverting application behavior. After destructive contract work, the removed data may need to be restored from a backup or reconstructed through a compensating migration. Plan recovery before dropping the old shape; do not treat rollback as automatic once cleanup has run.
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