AWS Database Blog
Category: Compute
How to stream PostgreSQL changes to Amazon S3 with AWS Fargate
In this post, we show you how to build a fully managed, event-driven change data capture (CDC) pipeline. It streams row-level changes from Amazon RDS for PostgreSQL or Amazon Aurora PostgreSQL to Amazon S3 in near real time. You deploy the entire pipeline with a single AWS CloudFormation template, and it can run in private subnets with no internet gateway without exposing resources to the public internet.
Monitor self-managed databases with Amazon CloudWatch Database Insights
Amazon CloudWatch Database Insights now extends to self-managed databases. Monitor self-managed PostgreSQL on Amazon EC2 alongside your Amazon Aurora and Amazon RDS fleet from a single console, with the same DB Load, Top SQL, and wait event analysis you use for managed databases.
Automated PII redaction for Amazon RDS for PostgreSQL audit logs
In this post, we show you how to deploy a serverless pipeline that creates an irreversibly redacted, queryable archive of Amazon RDS for PostgreSQL audit logs. The pipeline permanently removes Social Security numbers (SSNs), credit cards, email, names, and more than 30 types of personally identifiable information (PII) before storing clean logs in Amazon S3 for query through Amazon Athena.
Build a semantic ontology to power AI assistants on AWS – Part 1
In this post, we show you how to build a semantic ontology that helps your AI assistants navigate enterprise data efficiently. You’ll learn how to structure a property graph store for data relationships, set up vector indexing for semantic search, and implement an automated fact-learning layer that improves use. This bottom-up approach grounds your ontology in the data that exists, building abstractions from observed patterns rather than theoretical models.
User authentication and session management with Amazon Aurora DSQL
In this post, you learn how to design and implement a user authentication service with session management on Amazon Aurora DSQL. You see the full request flow from client to database and back, explore the design considerations specific to Amazon Aurora DSQL, and discover practical lessons from building and testing against a live cluster.
Building Financial Hierarchies with Amazon Neptune for Treasury Operations
In this post, we show how Amazon’s Finance Technology (FinTech) team uses Amazon Neptune to model complex corporate treasury structures as a property graph. These structures include the legal entity relationships, intercompany agreements, and bank account associations that govern payment routing and cash management.
Automate Amazon Aurora PostgreSQL major or minor version upgrade using AWS Systems Manager and Amazon EC2
Managing Aurora PostgreSQL-Compatible Edition upgrades across multiple database clusters can be time-consuming and error-prone when done manually. In this post, we show you how to automate Amazon Aurora PostgreSQL upgrades across your entire database fleet through consistent, repeatable procedures.
Oracle Database@AWS decoded: Determining the right fit for your Oracle workloads
In this post, we explore the key reasons why Oracle Database@AWS is a strong fit for organizations running Oracle workloads on AWS. We cover the business, technical, and licensing advantages it brings, and how it complements the existing AWS options you already know, such as Amazon RDS for Oracle and Amazon EC2.
AWS purpose-built database recovery: A guide to business continuity and disaster recovery strategies
This post addresses recovery challenges in multi-database architectures, focusing on both low-consistency and mission-critical scenarios. We explore practical strategies for implementing resilient recovery mechanisms across Amazon DynamoDB, Amazon Aurora, Amazon Neptune, Amazon OpenSearch Service, and other AWS database services.
Conversational Oracle EBS operations with CloudWatch MCP and Kiro CLI
In this post, you learn how to implement conversational operations for Oracle E-Business Suite (Oracle EBS) on AWS by connecting Kiro CLI with your monitoring infrastructure through the MCP. We walk through the technical architecture that enables natural language queries to retrieve CloudWatch metrics, analyze logs, and execute operational commands.









