Automate Oracle PL/SQL to PostgreSQL migration with Amazon Bedrock and Strands Agents
The growing demand for seamless database migration is driven by the need for businesses to adapt quickly to changing technology landscapes and stay competitive. As companies increasingly adopt cloud-native services, they require efficient and reliable tools to transition between different database systems. AWS's solution caters to this need by leveraging generative AI and automation to simplify the often manual and error-prone process of code conversion.
ANALYSIS: The adoption of AWS's solution will likely have implications for the database migration market, potentially disrupting traditional migration vendors. As more companies turn to AI-powered tools, we can expect to see increased competition and innovation in the space. Furthermore, the use of AWS Bedrock and Strands Agents may set a new standard for cloud-native migration tools, making it easier for businesses to adopt cloud services.
Key Takeaways
The solution enables businesses to automate up to 90% of the database migration process, reducing manual labor and minimizing the risk of human error.
The use of generative AI and automation in database migration is a significant trend that will continue to shape the industry in the coming years.
Companies that adopt AWS's solution may experience improved database scalability, flexibility, and cost savings due to the streamlined migration process.
About the Source
This analysis is based on reporting by AWS Database Blog. Here is a short excerpt for context:
In this post, you learn how to build a generative AI–powered migration assistant that helps automate portions of the last mile of code conversion. Using Anthropic’s Claude Sonnet 4.6 on Amazon Bedrock, the Strands Agents framework, and the AWS Knowledge MCP Server, you can automate the conversion and validation of PL/SQL objects against Amazon Aurora PostgreSQL-Compatible Edition. The assistant reads the AWS DMS SC assessment CSV, fetches live PL/SQL source from Oracle, converts each object, deploys the result to Aurora PostgreSQL through AWS Lambda, and runs automated tests, in a single pipeline.Read the original at AWS Database Blog
