AWS Database Blog

Category: Advanced (300)

How an AWS customer in the learning services industry migrated and modernized SAP ASE to Amazon Aurora PostgreSQL

In this post, we explore how a leading AWS customer in the learning services industry successfully modernized its legacy SAP ASE environment by migrating to Amazon Aurora PostgreSQL-Compatible Edition. Partnering with AWS, the customer engineered a comprehensive migration strategy to transition from a proprietary system to an open source database while providing high availability, performance optimization, and cost-efficiency.

Native SQL Server replication options on Amazon RDS Custom for SQL Server

In this post, we explore SQL Server replication implementation on Amazon RDS Custom. You’ll learn about different replication types supported on RDS Custom SQL Server, including snapshot, transactional, and merge replication, along with their specific use cases. Finally, we provide a step-by-step guide to setting up replication, from configuring the distributor to creating publications and managing subscriptions.

Implement row-level security in Amazon Aurora MySQL and Amazon RDS for MySQL

Row-level security (RLS) is a security mechanism that enhances data protection in scalable applications by controlling access at the individual row level. It enables organizations to implement fine-grained access controls based on user attributes, so users can only view and modify data they’re authorized to access. This post focuses on implementing a cost-effective custom RLS solution using native MySQL features, making it suitable for a wide range of use cases without requiring additional software dependencies. This solution is applicable for both Amazon Relational Database Service (Amazon RDS) for MySQL and Amazon Aurora MySQL-Compatible Edition, providing flexibility for users of either service.

Connect to Amazon RDS for Db2 using AWS CloudShell

Connecting to an Amazon RDS for Db2 instance has traditionally required spinning up an Amazon EC2 bastion host or running Db2 clients locally. With the new AWS CloudShell VPC integrated environments, you can now securely connect—with no Amazon EC2 required, no local installs, and no cost beyond normal Amazon RDS and AWS networking. In this post, we show you how to connect to Amazon RDS for Db2 using CloudShell.

Cross-account migration of Amazon RDS for SQL Server with column-level encryption

Organizations running SQL Server workloads on Amazon RDS sometimes need to migrate their databases to different AWS accounts. This migration becomes more complex when mission-critical data requires column-level encryption to meet compliance requirements. In this post, we demonstrate how you can migrate your symmetric key-encrypted database on Amazon RDS for SQL Server to another AWS account without compromising security. The solution we present can also help you implement symmetric key encryption on a new database in Amazon RDS for SQL Server.

Amazon DynamoDB zero-ETL integration with Amazon SageMaker Lakehouse – Part 2

Amazon DynamoDB zero-ETL integration with Amazon SageMaker Lakehouse allows you to run analytics workloads on your DynamoDB data without having to set up and manage extract, transform, and load (ETL) pipelines. In this post we cover setting up Amazon SageMaker Unified Studio, followed by running data analysis to showcase its capabilities. We illustrate our solution walkthrough with an example of a credit card company that wants to analyze its customer behavior and spending trends.

Amazon DynamoDB zero-ETL integration with Amazon SageMaker Lakehouse – Part 1

Amazon DynamoDB zero-ETL integration with Amazon SageMaker Lakehouse allows you to run analytics workloads on your DynamoDB data without having to set up and manage extract, transform, and load (ETL) pipelines. In this two-part series, we first walk through the prerequisites and initial setup for the zero-ETL integration. In Part 2, we cover setting up Amazon SageMaker Unified Studio, followed by running data analysis to showcase its capabilities. We illustrate our solution walkthrough with an example of a credit card company that wants to analyze its customer behavior and spending trends.

Streamline Amazon Aurora database operations at scale: Introducing the AWS Database Acceleration Toolkit

In this post, we introduce the AWS Database Acceleration Toolkit (DAT), an open source database accelerator. DAT is an infrastructure as code solution using Terraform to simplify and automate initial setup, provisioning, and on-going maintenance activities for Amazon Aurora.

Using the PostgreSQL extension tds_fdw to validate data migration from SQL Server to Amazon Aurora PostgreSQL

Data validation is an important process during data migrations, helping to verify that the migrated data matches the source data. In this post, we present alternatives you can use for data validation when dealing with tables that lack primary keys. We discuss alternative approaches, best practices, and potential solutions to make sure that your data migration process remains thorough and reliable, even in the absence of traditional primary key-based validation methods. Specifically, we demonstrate how to perform data validation after a full load migration from SQL Server to Amazon Aurora PostgreSQL-Compatible Edition using the PostgreSQL tds_fdw extension.

Real-time Iceberg ingestion with AWS DMS

Etleap is an AWS Advanced Technology Partner with the AWS Data & Analytics Competency and Amazon Redshift Service Ready designation. In this post, we show how Etleap helps you build scalable, near real-time pipelines that stream data from operational SQL databases into Iceberg tables using AWS DMS. You can use AWS DMS as a robust and configurable solution for change data capture (CDC) from all major databases into AWS.