Oracle to PostgreSQL on Azure: 2-4 Wks PoC

doubleSlash Net-Business GmbH

Examination of technical feasibility and implementation of a proof of concept

Based on the results of the "Assessment" phase, the "Proof of Concept" phase will examine the technical feasibility in order to identify and minimize possible sources of error. To this end, we select suitable data types and prepare them for a test migration from Oracle to PostgreSQL based on Azure. On this basis, functional tests can be carried out on the converted objects, which provide information about possible inconsistencies.

Our approach in the proof of concept phase:

Review and iterate from assessment:

  • Analysis: Comparison of the source and target data model and definition of the data mapping; data that is no longer relevant or qualitatively unusable is identified (including during the repeated production-related test iterations)

Proof of Concept:

  • Implementation: Migration tools are set up for the highest possible degree of migration automation
  • Test migration: Test data from the legacy or source system is converted, cleansed and, if necessary, completed for the target data system and then migrated to Azure

Services in the Proof of Concept include:

  • Selection of data types / sources for the test migration
  • Implementation of the migration engine according to ETL
    • Reading source data (Extract)
    • Cleanse, map and enrich data (Transform)
    • Write target data (Load)
  • Preparation of the target database with a focus on performance and a high degree of automation during implementation
  • Checking and converting incompatible objects
  • Test data migration

Duration: 2 - 4 weeks (depending on effort)

Terms, conditions, and pricing are custom to each engagement

https://store-images.s-microsoft.com/image/apps.24694.c20542ce-a8e7-4d37-a85a-25c1b0b4ac49.66958502-e210-482d-89c9-0e4d3b41ae0e.5431d1eb-a063-458e-93bf-1072690f3a09
https://store-images.s-microsoft.com/image/apps.24694.c20542ce-a8e7-4d37-a85a-25c1b0b4ac49.66958502-e210-482d-89c9-0e4d3b41ae0e.5431d1eb-a063-458e-93bf-1072690f3a09