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Oracle OS · Oracle Database → Databricks · Migration

Proven Oracle to Databricks Migrations—Fixed Scope, Senior Engineers

Migrating Oracle Database to Databricks is a well-understood project. We convert PL/SQL, ETL, and analytical datasets to Delta Lake with a fixed scope and timeline, so your team stays focused on business outcomes.

Get My Free AssessmentGet a clear, low-commitment assessment of what your migration will cost and how long it will take.

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Get a clear, low-commitment assessment of what your migration will cost and how long it will take.

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Powered by the 3PS Migration Engine

The lowest-cost way off Oracle Database: our migration tooling automates the repetitive work —you pay senior engineers for judgment, not keystrokes.

Automated discovery
Your Oracle Database estate mapped — workloads, dependencies, licensing — before day one
Conversion tooling
Schema, config and workload translation to Databricks, automated where it's safe
Parity validation
Side-by-side testing proves Databricks matches production before cutover
Runbook cutover
Rehearsed, reversible, scheduled in your maintenance window
40-70%
Savings vs. Oracle vendor support renewals
6-12 months
Typical project duration
4-6
Senior consultants assigned per project, no junior engineers

How we support Oracle Database → Databricks after migration

  • Senior platform engineers run every migration—no junior staff.
  • Fixed scope and budget: $150K–$1.3M, 6–12 months.
  • Legacy Oracle stays under vendor support during the move.
  • Third-party support covers operational issues if vendor renewal lapses.
  • Post-migration: Databricks cluster optimization & Lakehouse managed services.
  • 40-70% savings on legacy Oracle support while you plan the transition.

Nested PL/SQL logic too complex to convert?

Our engineers have refactored millions of lines of deeply nested Oracle PL/SQL. We map each procedure to Databricks SQL or PySpark—no manual guesswork.

High-frequency updates/deletes breaking your migration?

Transactional schemas with frequent MERGE/UPSERT patterns are tricky. We design incremental Delta Lake merge strategies that preserve data integrity without stalls.

Dreading a forced big-bang cutover?

You don't have to flip a switch. Keep Oracle running under its existing support contract until your Databricks environment is fully validated. Migrate on your timeline.

Oracle Database → Databricks migration — your questions answered

What happens to my Oracle support contract during the migration?+

Your Oracle Database stays under vendor support for as long as your contract is active. There is no forced cutover. If the contract lapses before migration finishes, our independent third-party support covers most operational issues on the legacy platform—but it is not vendor support and does not include Oracle patches.

How do you handle Oracle Database triggers in the migration?+

We analyze each trigger's purpose (enforcement, auditing, derived data) and redesign the equivalent behavior in Databricks using Delta Live Tables or application-level logic. Complex triggers are handled case by case in the fixed scope.

Can I merge unstructured data with my Oracle Data Warehouse migration?+

Yes. The Databricks Lakehouse unifies structured, semi-structured, and unstructured data. We build Delta Lake schemas that accommodate both your existing Oracle tables and new data sources like logs, JSON, or images.

What triggers an Oracle to Databricks migration for most enterprises?+

Common triggers include: need for advanced machine learning on the same data platform, Exadata lease termination, or a business decision to merge structured and unstructured analytics. Our feasibility workshop helps you confirm the right timing and approach.

Move from Oracle to Databricks with Confidence—Fixed Scope, No Surprises

You don't need a risky big-bang migration or inflated vendor bills. Our senior engineers convert your Oracle Database ETL, analytical datasets, and PL/SQL to Databricks Lakehouse on a fixed budget. After migration, we optimize clusters, build Spark pipelines, and manage your Lakehouse—so you can focus on AI and analytics, not infrastructure.

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