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A collection of technical articles and blogs published or curated by Google Cloud Developer Advocates. The views expressed are those of the authors and don't necessarily reflect those of Google.

Overcoming AWS SCT Extension Pack Limitations for Faster Migration to Google Cloud Databases

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Google Cloud Database for PostgreSQL offers multiple options, including Cloud SQL Edition, Cloud SQL Enterprise Edition, and AlloyDB. Each option brings significant value propositions for managing databases with ease and at scale to meet demands. AlloyDB is a next-generation database with a modern architecture featuring disaggregated compute and storage, support for HTAP workloads, Vector Embedding, Vertex AI integration, and more.

Google Cloud Database Migration Services (DMS) facilitate the migration of databases from on-premises or another cloud to PostgreSQL options on Google Cloud. However, when migrating databases from the AWS platform, such as RDS or Amazon Aurora, DMS has limitations. Migration is not supported if the source database uses any of the AWS SCT Extension Packs (aws_oracle_ext, aws_sqlserver_ext, aws_mysql_ext, aws_postgresql_ext).

DMS Limitation — AWS SCT Extension Pack

In this blog, we’ll delve into strategies to mitigate these limitations and expedite the migration process from AWS databases to Google Cloud.

What is AWS SCT Extension Pack

An Extension is primarily introduced as part of the conversion process from a commercial engine like Oracle or SQL Server to an open-source compatible option like PostgreSQL when using the AWS Schema Conversion Tool (SCT) in AWS for migrating to RDS or Amazon Aurora. It serves to conceal the procedural complexity by utilizing wrapper code defined within extensions stored as schemas, such as aws_oracle_ext, aws_sqlserver_ext, and others.

Solution — Open Source Extension Dependency Assessment tool

Using open-source extension assessment tool, you can scan the migrated code in PostgreSQL and capture underlying usage patterns and dependencies with various extension pack functions and present it in a report(sample report).

By analyzing the usage patterns, we can categorize the dependency on the extension pack as Simple, Medium, or Complex with functional category. This categorization helps to highlight the efforts required to address extension dependencies and resolve them using native PostgreSQL solutions like Orafce or native functionality.

For further details, do check out here.

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Google Cloud - Community
Google Cloud - Community

Published in Google Cloud - Community

A collection of technical articles and blogs published or curated by Google Cloud Developer Advocates. The views expressed are those of the authors and don't necessarily reflect those of Google.

Deepak Mahto
Deepak Mahto

Written by Deepak Mahto

Database Migration Expert - Enabling success with PostgreSQL on Cloud.

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