Migrations/Oracle → Snowflake
Oracle to Snowflake Migration
Oracle migrations are as much a licensing and lock-in escape as a technical one. The hard part isn't the data — it's the decades of PL/SQL, materialized views, and Oracle-specific behavior the business quietly depends on. We run the move as a controlled engineering discipline, validating fidelity at every step.
Why teams migrate
The triggers we hear most
- 01Oracle licensing and support renewals have become a hostage negotiation
- 02Analytical workloads are competing with operational ones on the same expensive box
- 03PL/SQL packages encode business rules nobody has documented in years
- 04You want cloud elasticity and a stack your team can actually hire for
- 05A compliance or end-of-life deadline is forcing the platform decision
What makes it tricky
Where Oracle-to-Snowflake migrations go wrong.
PL/SQL and packages don't lift-and-shift
Packages, materialized views, and PL/SQL procedures carry logic that has to be re-expressed in dbt/SQL and orchestration — and validated, because subtle NULL-handling and date semantics differ between Oracle and Snowflake.
Number and date fidelity
Oracle's NUMBER precision, DATE-with-time behavior, and implicit conversions don't map cleanly. We reconcile aggregates and distributions, not just counts, to catch the rounding and coercion bugs these introduce.
Sequences, triggers, and hidden coupling
Sequences, database triggers, and DBLink dependencies create coupling that isn't visible in the schema. Surfacing it before cutover is what separates a clean migration from a painful one.
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
Map the Oracle estate — schemas, packages, materialized views, triggers, jobs, and downstream consumers — into a verified dependency graph.
- 2
Re-express PL/SQL business logic as version-controlled dbt/SQL and orchestration, designed for Snowflake's compute model.
- 3
Dual-run Oracle and Snowflake, reconciling aggregates and distributions automatically until they agree.
- 4
Migrate by subject area, retiring the highest-cost Oracle workloads first to bank savings early.
- 5
Cut over on evidence with a scripted rollback, then set the Oracle side read-only and decommission on a held date.
Analytical workloads running on elastic Snowflake compute, the irreplaceable PL/SQL logic re-homed in code your team owns, and the Oracle licensing line on a path to zero.
FAQ
Common questions
- Do we have to rewrite all our PL/SQL?
- Not blindly. We catalog what actually runs the business, translate that logic into version-controlled dbt/SQL and orchestration, and delete the dead weight — typically a meaningful share of a long-lived Oracle estate has no downstream consumer at all.
- How do you keep the numbers identical through an Oracle migration?
- Automated reconciliation on aggregates and distributions — not just row counts — running while both systems are live, so type-coercion and NULL-handling differences surface before cutover rather than after.
- Can we cut Oracle licensing costs before the full migration is done?
- Usually yes. We migrate by subject area and retire the highest-cost workloads first, so savings start accruing well before the last slice cuts over.
→ Start a project
Planning a Oracle to Snowflake 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.