# Amazon Aurora Machine Learning

> Amazon Aurora Machine Learning provides managed vector storage and search capabilities integrated into Aurora PostgreSQL for AI workloads on AWS. Key features include serverless scaling, direct ML model calls via SQL for embeddings, and seamless integrations with Bedrock and SageMaker. Perfect for RAG pipelines and enterprise AI applications, it simplifies vectorization and abstracts infrastructure compared to self-hosted options like Milvus.

- **URL:** https://aws.amazon.com/rds/aurora/machine-learning/
- **Category:** Managed Serverless Vector DBs
- **Tags:** machine-learning, Embeddings, Aws, Serverless Scaling, Enterprise RAG, Auto Indexing
- **Featured:** yes
- **Updated:** 2026-04-22 13:39
- **Canonical page:** https://vectordb.ever.works/items/amazon-aurora-machine-learning

## Details

## Amazon Aurora Machine Learning

Amazon Aurora Machine Learning is a feature of Amazon Aurora that integrates machine learning capabilities directly into the database. It allows users to invoke ML models, such as Amazon Bedrock or Amazon SageMaker, by using SQL functions.

### Features

*   **SQL-driven ML Model Calls:** Enables making direct calls to external machine learning models like Amazon Bedrock and Amazon SageMaker through SQL functions.
*   **Direct Embedding Generation:** Supports the generation of embeddings directly within the database environment.
*   **Vectorization Abstraction:** Simplifies the process of working with vector data by abstracting the complexities of vectorization.

### Pricing

Pricing information for Amazon Aurora Machine Learning is not detailed in the provided content.

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