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Data Migration

Migrate from on-prem to cloud or legacy to modern stacks with zero downtime.

The problem

Your legacy database is slow, expensive, and risky. You need to migrate without breaking production.

Our approach

1

Assessment: Analyze schema, data volume, dependencies, and downtime tolerance.

2

Planning: Design migration strategy (big bang, phased, dual-write) with rollback procedures.

3

Execution: Migrate data with validation at every step. Monitor performance and integrity.

4

Cutover: Switch traffic to new system with minimal downtime. Keep old system as fallback.

Outcomes

Zero-downtime migration (or minimal planned window)

Data validation and integrity checks

Rollback procedures if issues arise

Performance benchmarks (before/after)

Sample deliverables

  • Migration scripts and ETL pipelines
  • Data validation reports
  • Rollback and disaster recovery plans
  • Performance benchmarks and monitoring
  • Handover documentation

Timeline

6–12 weeks depending on data volume and complexity.

Tech stack

PythonAirflowdbtPostgreSQLMySQLMongoDBSnowflakeBigQuery

FAQs

Can you guarantee zero downtime?

In most cases, yes. We use dual-write strategies and phased cutover.

What if something goes wrong?

We have rollback procedures and keep the old system running until cutover is validated.

How do you validate data integrity?

Row counts, checksums, and sample comparisons at every migration phase.

Ready to get started?

Book a thirty minute technical scope call. We will review your requirements and respond with a timeframe and estimate.

Request a scope call