Database Migration & ETL Services
Moving your data to a new database or platform without the silent corruption that only shows up after go-live.
Database migrations fail quietly more often than they fail loudly. A field gets truncated by a type mismatch. A timezone conversion silently shifts timestamps. A batch of records drops during an ETL job that logs "success" because it completed without an error, not because it moved everything correctly. Nobody notices until a report looks wrong weeks later, and by then the source data may already be gone.
We treat data migration as its own project with its own validation discipline, not a step tucked inside an application migration. Every migration includes record-level checks comparing source and destination, because "the migration script finished" and "the data is correct" are two different claims, and we don't let the first one stand in for the second.
What's Included
Data mapping and schema audit
A documented mapping between source and target schemas, including every field transformation, type conversion, and edge case identified before migration starts.
ETL migration plan
A staged plan for extracting, transforming, and loading the data, including how referential integrity and dependencies between tables get preserved through the process.
Data validation report
A record-level comparison between source and destination data, documenting exactly what moved correctly, what was flagged, and how discrepancies were resolved before go-live.
Rollback and recovery plan
A documented path back to the source data and system if the migration needs to be reversed, so a bad migration is a delay, not a catastrophe.
Our Approach
Map the schema before we move a single row.
We document every field, type, and relationship between source and target before touching data — including the edge cases that don't fit cleanly, like inconsistent date formats or fields that were repurposed years ago.
Validate every record, not a sample.
Wherever feasible, we run full record-level comparisons between source and destination after migration, not a spot check on a handful of rows. Data integrity is not something we estimate.
Keep the source intact until validation is signed off.
We don't decommission or overwrite the source system until the destination has been validated and confirmed correct, so there's always a way to recover if something was missed.
Frequently Asked Questions
Record-level validation — comparing row counts, checksums, and key field values between source and destination after every migration batch, not just after the full job completes. Discrepancies get flagged and resolved before the source system is retired, so gaps surface in our validation report, not in your reports months later.
We handle migrations between common relational databases (MySQL, PostgreSQL, SQL Server, Oracle), moves to and from NoSQL platforms, and ETL pipelines into cloud data warehouses. If your combination is unusual, tell us in the initial conversation and we'll give you an honest read on scope.
Both. Some projects are a one-time cutover from an old database to a new one. Others need an ongoing ETL pipeline feeding a data warehouse or analytics platform. We scope which one you actually need — a lot of "we need a migration" requests turn out to be a recurring pipeline problem in disguise.
A focused migration for a single database with moderate data volume and validation typically runs ₹6-12 lakh over 6-10 weeks. Larger migrations with multiple source systems, complex transformations, or ongoing ETL pipeline builds run higher. We scope precisely after the schema audit, not before.
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