AWS Database Blog

Rebuild large indexes on Aurora PostgreSQL with Blue/Green Deployments

In this post, we show how to rebuild large indexes on Amazon Aurora PostgreSQL by combining Amazon Aurora Blue/Green Deployments with Aurora Optimized Reads. By performing the reindex on the green (staging) environment with a Non-Volatile Memory express (NVMe)-backed instance class, the sort phase uses fast local storage instead of Amazon EBS over the network, and you avoid impacting production workloads.

Provisioning DMS Schema Conversion via AWS CloudFormation

AWS Database Migration Service Schema Conversion (DMS SC) converts database objects across heterogeneous systems such as Oracle or SQL Server to PostgreSQL or MySQL. In this post, we show you how DMS SC, with generative AI capabilities, elevates the code conversion experience.

Accelerate database modernization with agentic AI in AWS DMS Schema Conversion

Accelerate database modernization with agentic AI in AWS DMS Schema Conversion

Starting today, you can use AI agents to orchestrate entire AWS DMS Schema Conversion (DMS SC) workflows through natural language. An AI agent manages the full lifecycle, including creating migration projects, browsing source metadata, converting schemas, generating assessment reports, and exporting results, all from a conversational prompt.

Diagnose and resolve replica lag in Amazon RDS for Oracle replicas – Part 2

This post is the second in a two-part series on reducing replication lag for Amazon RDS for Oracle Read Replicas. In Part 1, we discussed redo compression and configuration options to optimize replica lag. In this post, we show you how to monitor replica lag using Amazon CloudWatch metrics and database views, identify common root causes through wait event analysis, and how to troubleshoot and resolve performance issues.

Logical replication improvements in Amazon RDS for PostgreSQL 18

In this post, we demonstrate how to use the PostgreSQL 18 logical replication improvements on RDS for PostgreSQL: replicating STORED generated columns with the publish_generated_columns parameter, monitoring conflicts through the new counters in pg_stat_subscription_stats, verifying that parallel streaming is enabled by default, toggling two-phase commit on a running subscription, and configuring idle_replication_slot_timeout for automatic slot cleanup. These features are available on RDS for PostgreSQL 18.0 and later and Aurora PostgreSQL.

Automate PostgreSQL audit log extraction and analysis with Amazon S3

Automate PostgreSQL audit log extraction and analysis with Amazon S3

In this post, we show you how to deploy an automated pipeline that extracts PostgreSQL audit logs from CloudWatch Logs, converts them into structured comma-separated values (CSV) format, and stores them in Amazon S3 for long-term analysis. The solution processes log entries in near real time after generation.

Dynata’s journey to lower TCO and faster modernization with AWS Database Savings Plans

In this post, we show how Dynata simplified database cost optimization and accelerated modernization to AWS Graviton processors by adopting Database Savings Plans. Rather than managing Reserved Instances across multiple database services, Dynata consolidated their cost commitment into a single, flexible pricing model. This reduced operational overhead by 70%, extended cost coverage to Amazon Aurora serverless, and lowered total cost of ownership as their infrastructure evolved.