Migrations/On-prem → Cloud warehouse
On-Prem to Cloud Data Warehouse Migration
Getting a data warehouse out of your own data center is as much a security and networking project as a data one. Between our founders we've run cloud platform builds across AWS, Microsoft Azure, and Snowflake — so we design the move around your compliance posture and target cloud, not a one-size template.
Why teams migrate
The triggers we hear most
- 01Hardware refresh cycles and data-center costs you'd rather stop paying
- 02On-prem can't elastically scale for spiky analytical workloads
- 03Security and DR are harder and more expensive to do well on-prem
- 04Your team wants modern cloud tooling and a stack they can hire for
- 05A cloud-first or cloud-exit mandate is now on the roadmap
What makes it tricky
Where On-prem data warehouse-to-Cloud (Snowflake, Azure, or AWS) migrations go wrong.
Network, identity, and security come first
Private connectivity, identity federation, key management, and data-residency rules have to be designed before a byte moves. On Azure that's one shape; on AWS or Snowflake another. We design to your target and your compliance posture.
Moving terabytes is a plan, not a copy
Initial bulk load plus change-data-capture to keep the cloud in sync while the on-prem system stays live — so cutover is a switch, not a multi-day freeze.
Egress, cost, and the long tail
Data-egress fees, right-sized compute, and the on-prem integrations that assumed a flat local network all need handling — the last 20% of integrations is where naive cloud migrations stall.
How we run it
Parallel-run, reconciliation-gated, reversible.
The same migration discipline our founders ran inside enterprise data teams — the evidence decides each cutover, not the calendar.
- 1
Assess the on-prem estate and target cloud (Snowflake, Azure, or AWS), and design the network, identity, and security foundation first.
- 2
Stand up the cloud platform as infrastructure-as-code, with cost controls and DR built in.
- 3
Bulk-load history, then run change-data-capture so the cloud stays current while on-prem keeps serving.
- 4
Reconcile automatically, migrate consumers and integrations by subject area, and rehearse the cutover.
- 5
Cut over on evidence with a rollback path, then decommission the on-prem footprint on a held date.
A cloud data platform sized to your workloads with security and DR done properly, the on-prem warehouse retired, and infrastructure your team can evolve as code.
FAQ
Common questions
- Which cloud should we migrate our warehouse to?
- It depends on your existing footprint, compliance posture, and team. We've built on Snowflake, Microsoft Azure, and AWS, and the diagnostic includes a target recommendation with the trade-offs spelled out — rather than defaulting to whichever one we sell.
- How do you migrate terabytes without a long outage?
- Bulk-load the history once, then run change-data-capture so the cloud platform stays in sync while the on-prem system keeps serving. Cutover becomes a brief switch with a rollback, not a multi-day freeze.
- How do you handle security and compliance in the move?
- Network connectivity, identity federation, key management, and data-residency are designed before any data moves — to your compliance requirements and your target cloud — because retrofitting security after a migration is how breaches happen.
→ Start a project
Planning a On-prem data warehouse to Cloud (Snowflake, Azure, or AWS) migration?
Describe your current estate in three sentences. We'll come back with how we'd phase it, what it likely costs, and whether we're the right team — usually within two business days.