Database Migration Between Servers

Migration goals and scope

Start by stating why you are migrating and what success looks like. Define clear goals such as reducing costs, improving performance, or consolidating systems. Set measurable targets: acceptable downtime, target throughput, and data consistency levels.

List what will move and what will stay. Include databases, applications, middleware, and dependent services. Identify stakeholders and assign owners for each part of the migration. A clear scope prevents surprises and scope creep.

Inventory and environment assessment

Inventory every asset that touches the data and application. Record versions, configurations, network addresses, storage sizes, and dependencies. Include:

• Database engines and versions.
• Application servers and libraries.
• Scheduled jobs, cron tasks, and integrations.
• Network topology, firewalls, and load balancers.

Measure current performance: average and peak CPU, memory, I/O, and latency. Capture baseline metrics for later comparison. Note security requirements like encryption, access controls, and compliance rules.

Compatibility and version checks

Check software compatibility between source and target environments. Confirm database engine and driver compatibility, SQL dialect differences, and supported data types.

Review stored procedures, triggers, views, and extensions for behavior changes. Verify client tools and ORMs will work with the new version. Test a simple query set on the target to detect syntax or behavior differences early.

Document any required code changes and prioritize fixes that block migration. Plan for testing of features that depend on specific engine behavior, such as transaction isolation or optimizer changes.

Backup and disaster recovery planning

Create full backups before any migration step and verify you can restore them. Backups should include data, schema, configuration files, and any custom scripts. Keep backups in at least two separate locations.

Test restores on a separate environment to confirm data integrity and recovery time. Define recovery point objective (RPO) and recovery time objective (RTO). If you cannot meet them with simple backups, add replication or change-data-capture (CDC) to limit data loss.

Plan for a documented rollback procedure and make sure you can reach it quickly during cutover. Ensure permissions and encryption keys are preserved and transferable.

Migration strategy selection

Choose a migration approach based on your goals and constraints:

• Rehost (lift-and-shift): Move as-is. Fast but may carry technical debt.
• Replatform: Make small improvements (OS, engine patching) without changing code.
• Refactor: Change application or schema to use new features. Slower but offers long-term gains.
• Hybrid: Combine methods for different components.

For minimal downtime, consider replication-based approaches, blue-green deployment, or rolling upgrades. Weigh cost, complexity, and risk to pick the best fit.

Target server provisioning and configuration

Provision target servers with the right size and network access. Match CPU, RAM, disk type (SSD vs HDD), and IOPS to your measured needs plus headroom for growth.

Configure the OS, kernel parameters, database settings, and security controls. Tune storage and filesystem settings for database workload. Set up monitoring, logging, users, and access controls before importing data.

Automate provisioning with IaC tools like Terraform or Ansible to ensure repeatability. Keep configuration as code to simplify audits and future changes.

Schema migration and transformation

Compare source and target schemas and prepare migration scripts. Use tools that produce ordered, idempotent migrations (for example, Flyway or Liquibase). Handle these items:

• Data type differences and precision changes.
• Indexes, constraints, and foreign keys.
• Collation and character set mismatches.
• Stored procedures, triggers, and functions.

Test schema migrations on a copy of production. If transformation is needed (renaming fields, splitting tables), create mapping documents and transformation scripts. Validate that migrations run cleanly and that rollbacks are possible.

Data export, transfer, and import methods

Choose between physical and logical transfer methods.

Logical export/import:

• Tools like pg_dump, mysqldump, or export APIs.
• Good for platform changes and schema transformations.
• Slower for large datasets; use parallel options where available.

Physical transfer:

• File-level copy of database files or snapshots.
• Faster for very large volumes.
• Requires same engine version and compatible storage setup.

Use streaming replication or CDC to minimize downtime by syncing live changes to the target. For cloud moves, consider object storage (S3, GCS) as a transit or AWS Database Migration Service and similar managed tools.

Ensure network bandwidth and security (VPN, encryption) are in place for large transfers. Monitor transfer progress and plan for re-syncs of any deltas.

Data validation and integrity verification

After transfer, verify that data on the target matches the source. Use row counts, checksums, and sampled queries to detect differences. Methods include:

• Row counts per table and per partition.
• Hash or checksum per row or per batch.
• Keyed checksums for large tables to reduce cost.
• Application-level acceptance tests to confirm behavior.

Validate constraints and foreign key relationships. Check indexes and query plans for regressions. Log any mismatches, investigate root causes, and re-transfer only affected segments when possible.

Cutover execution and minimizing downtime

Plan the cutover steps in detail and rehearse them. Typical cutover flow:

1. Final sync via replication or CDC.
2. Quiesce writes on source (put app in read-only or maintenance mode).
3. Apply remaining changes to target and validate.
4. Switch application connections (DNS, load balancer, or connection string).
5. Run smoke tests and monitor.

To reduce downtime, use incremental syncs and a short maintenance window for the final switch. Blue-green deployments let you switch traffic instantly. Rolling cutovers change small portions of traffic at a time to limit user impact.

Communicate the schedule to stakeholders and have a standby rollback plan with estimated durations.

Post-migration testing and monitoring

Run functional, performance, and security tests immediately after cutover. Confirm that critical user flows work and that background jobs run correctly.

Compare performance metrics to baseline: latency, throughput, and error rates. Tune configuration and queries where needed. Keep monitoring and alerting active to catch regressions quickly.

Schedule follow-up checks for data consistency and integrity over the next few days. Capture lessons learned and update runbooks based on actual issues encountered.

Rollback, cleanup, and documentation

Have a clear rollback plan before you start the migration. A rollback might mean switching traffic back to the original servers and replaying recent updates from backups. Test rollback procedures in advance.

After a successful migration, decommission old servers according to your security policy. Remove sensitive data, revoke access, and archive backups as required.

Document everything: the migration plan, scripts, issues encountered, fixes applied, and updated architecture diagrams. Store runbooks and contact lists for future reference. This documentation makes future migrations easier and reduces risk.

This guide focuses on practical steps and checks you can apply to most database or server migrations. Plan carefully, test thoroughly, and keep communication open throughout the process to reduce surprises and downtime.