AWS Database Blog

Category: Python

Automate the schema validation process for multiple databases like SQL Server, Oracle, PostgreSQL, and MySQL databases using Python

In the post, Validate database objects post-migration from Microsoft SQL Server to Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL, we explained the manual process to run relevant queries at source and target and match the output to identify the gaps post-migration. Because it’s a tedious job to validate all the available database objects, table […]

Transform and migrate data from a relational to non-relational database using an AWS Glue Spark ETL job

This post describes a methodology to transform and migrate data from a relational database like Amazon Relational Database Service (Amazon RDS) for MySQL to a non-relational database like Amazon DocumentDB (with MongoDB compatibility) using AWS Glue.

Analyzing the impact of Python version on Amazon DynamoDB scan performance

Amazon DynamoDB is a NoSQL database that allows for a flexible schema. This means that items in the same table may differ from each other in terms of what attributes are present for each item. In an earlier AWS Blog post, we looked at the performance impact of attribute counts per item. Recently, when helping […]

Python code to download DMS Task Logs using the AWS DMS Task ID

With AWS Database Migration Service (AWS DMS), you can migrate databases to AWS quickly and securely. In this post, we walk through the sample Python code required to download AWS DMS task logs on to your local computer using the AWS DMS task ID. Overview The DMS task logs contain task information logged during the […]