Automating vector embedding generation from Amazon Aurora PostgreSQL to Amazon Bedrock

The post describes automating vector embedding generation from Aurora PostgreSQL to Amazon Bedrock using pgvector and Bedrock models.

It outlines five implementation approaches with trade-offs in complexity, latency, reliability, and scalability.

The examples use Amazon Titan embeddings (1,536 dimensions) and provide a GitHub repo with AWS CDK, SQL, and Lambda code.