A QLDB Cheat Sheet for MySQL Users

The AWS ledger database (QLDB) is an auditors best friend and lives up to the stated description of “Amazon QLDB can be used to track each and every application data change and maintains a complete and verifiable history of changes over time.”

This presentation will go over what was done to take a MySQL application that provided auditing activity changes for key data, and how it is being migrated to QLDB.

While QLDB does use a SQL-format for DML (PartiQL) , and you can perform the traditional INSERT/UPDATE/DELETE/SELECT, the ability to extend these statements to manipulate Amazon Ion data (a superset of JSON) gives you improved capabilities and statements.

Get a comparison of how to map a MySQL structure multiple tables and lots of columns into a single QLDB table and then benefit with an immutable and cryptographically verifiable transaction log. No more triggers, duplicated tables, extra auditing for abuse of binary log activity.

We also cover the simplicity of using X Protocol and JSON output for data migration, and the complexity of AWS RDS not supporting X Protocol.

Tagged with: Amazon Web Services (AWS) Cloud Computing MySQL QLDB

Related Posts

Creating a More Realistic Benchmark

Common benchmark approaches fall into two general categories, synthetic testing and realistic testing. You have the most generic operations from a synthetic test, starting with the most simple example using a single table, a single column, and for a single DML operation.

Read more

Testing, Benchmarking, Evaluating

Testing and benchmarking are widely used terms in software technology, each serving a distinct purpose and goal. With the increasing adoption of AI in software development, the term evaluating has become significant and with this the re-emergence of what is quality assurance.

Read more

Your Attack Vector Extends Beyond Production Systems

A common data security issue is the unprotected copying of production data to non-production environments without any redaction, masking, or filtering. This practice poses a serious risk. A malicious actor will target the weakest link in your infrastructure, including non-production accounts and the developer systems accessing them.

Read more