01
Dual-Write Mode
Run your legacy and new Genedata systems in parallel during transition — zero disruption to downstream consumers.
Solutions · MigrationGENEDATA / 01
A new foundation.A considered transition.
Move one workload at a time. Connect existing sources, check parity, and carry governance into the new operating model.
Shared context · Lineage · Governance
Connected
Your sources
Existing sources
Legacy pipelines
Business definitions
Connected intelligenceMigration workflow
Governance
Business impactValidated workloads
Shared contextLineageGovernance
02
Data Validation
Automated byte-level comparison confirms migration fidelity before any production cutover is approved.
03
Phased Rollout
Migrate by data domain on your schedule with configurable cutover windows and instant rollback capability.
Built On
The products behind this solution.
A migration is a risk-management exercise, so the platform's job is to prove equivalence before anything is decommissioned.
GeneFlow
Runs dual-write from your existing sources so legacy stays authoritative while the replacement shadows it.
Learn moreGeneCatalog
Discovers the undocumented consumers from query logs — the ones that break a cutover nobody planned for.
Learn moreCortex SQL
Recomputes business metrics on both sides so equivalence is demonstrated semantically, not just byte-wise.
Learn moreCortex AI
Classifies and clusters divergences so recurring causes are addressed rather than triaged one by one.
Learn moreCutover Model
Both systems live until one is provably redundant.
The risk in a migration is not the copy — it is the moment of switching. Dual-write keeps legacy authoritative while Genedata runs alongside it, and a continuous comparator proves equivalence under real production load before anyone is asked to approve a cutover.
Migration Path
Assess, shadow, prove, cut over.
Each domain moves independently, so a problem in one is contained rather than stalling the whole programme.
Assess and score risk
Inventory sources, consumers, and undocumented dependencies, then sequence domains by risk and blast radius.
Shadow with dual-write
Writes land in both systems while legacy stays authoritative. Consumers see no change during this phase.
Prove equivalence
A continuous comparator checks row counts, values, and aggregates, so parity is demonstrated under real load rather than in a test window.
Cut over reversibly
Move consumers per domain with dual-write still running, so rollback is a routing change rather than a restore.
Risk Controls
The controls that make cutover a non-event.
Migrations fail on the things nobody documented. These controls are aimed at discovering those before they matter.
Dependency discovery
Query logs are analysed to find the consumers nobody remembered, including the report a regulator depends on.
Continuous comparison
Row counts, checksums, and business aggregates compared on every cycle, with divergence raised immediately.
Instant rollback
Because dual-write continues past cutover, reverting a domain is a routing change with no data reconstruction.
Semantic equivalence checks
Beyond byte comparison, key business metrics are recomputed on both sides and reconciled to catch logic drift.
Domain-by-domain sequencing
Each domain has its own cutover window and approval, so scope stays contained and reversible.
Historical backfill validation
Migrated history is validated against the legacy system across time, not just from the cutover date forward.
Who Benefits
Who this is for.
A migration is approved by people who mostly want assurance that nothing will break.
Platform Owner
Decommission with evidence
Retire legacy infrastructure only after the replacement has demonstrated parity under production load for an agreed period.
Decommissioning backed by a comparison record.
Downstream Consumer
Notice nothing
Reports and applications keep reading their existing interface throughout, and switch only when their domain is proven.
No coordinated big-bang cutover weekend.
Risk / Audit
Approve against proof
Review continuous parity evidence and a documented rollback path rather than a migration plan and assurances.
Sign-off based on demonstrated equivalence.
What Changes
What changes versus a conventional migration.
Most migration risk comes from treating cutover as a single irreversible event.
| Dimension | Before Genedata | With Genedata |
|---|---|---|
| Cutover | A coordinated weekend with everything moving at once | Per-domain, on your schedule, individually reversible |
| Validation | Sampled checks in a test environment | Continuous comparison under production load |
| Rollback | Restore from backup and replay | A routing change, because dual-write is still running |
| Unknown consumers | Discovered when their report breaks | Found in query-log dependency analysis beforehand |
| Downtime | A planned outage window | None — legacy stays live until it is redundant |
ZeroDowntime Target
Byte-levelValidation
InstantRollback
Per domainCutover Unit
The next step
Modernise without the risk.
The migration framework has modernised over 80 enterprise data stacks with zero recorded data loss events — because nothing is decommissioned until the replacement has been proven equivalent under production load.
FAQ
Migration, answered.
What platform owners and risk functions ask before committing to a cutover.
How long does a migration take?
It varies with estate size, but the sequencing matters more than the duration: each domain cuts over independently, so value arrives throughout rather than at the end of a multi-quarter programme.
What is the actual downtime?
None, by design. Legacy remains live and authoritative until the replacement has demonstrated parity under production load, and cutover moves consumers rather than switching systems off.
How is rollback handled?
Because dual-write continues past cutover, reverting a domain is a routing change rather than a restore from backup. That is what makes cutover a reversible decision instead of a one-way door.
How do you find consumers nobody documented?
Query-log analysis surfaces every reader of a dataset, including the quarterly report a regulator depends on that appears in nobody's architecture diagram.
What evidence does risk get before approving?
Continuous comparison results — row counts, checksums, and recomputed business metrics — gathered under production load, plus a documented rollback path.
Related content
Take the next step
Get a risk-scored roadmap.
Book a two-hour assessment and receive a sequenced plan for your specific legacy estate.