Cache synchronization using jOOQ and PostgreSQL functions
Introduction In this article, we are going to see how we can achieve cache synchronization with the help of jOOQ and PostgreSQL functions. By using Change Data Capture, we can track how table records change over time and synchronize the application-level cache entries that were built from the table records in question.
SQL Server audit logging using triggers
Introduction In this article, we are going to see how we can implement an audit logging mechanism using SQL Server database triggers to store both the previous and the current state of a given target table record in JSON column types.
PostgreSQL audit logging using triggers
Introduction In this article, we are going to see how we can implement an audit logging mechanism using PostgreSQL database triggers to store the CDC (Change Data Capture) records. Thanks to JSON column types, we can store the row state in a single column, therefore not needing to add a new column in the audit log table every time a new column is being added to the source database table.
MySQL audit logging using triggers
Introduction In this article, we are going to see how we can implement an audit logging mechanism using MySQL database triggers to store the old and new row states in JSON column types.
How to intercept entity changes with Hibernate event listeners
Introduction In this article, we are going to see how the Hibernate event listeners work and how you add your custom listeners to intercept entity changes and replicate them to other database tables. Recently, one of my blog readers asked a very good question on StackOverflow. Since my main goal as a Hibernate Developer Advocate is to help Java developers get the most out of JPA and Hibernate, I decided that this is a good opportunity to talk about the Hibernate event listener mechanism.
The best way to implement an audit log using Hibernate Envers
Introduction In this article, we are going to learn what is the best way to implement an audit log to track INSERT, UPDATE, and DELETE statements using Hibernate Envers. As previously explained, CDC (Change Data Capture) is an essential step to extract change events from an OLTP application to make them available to other modules in an enterprise system (e.g. caches, data warehouse). While Debezium is the most efficient way of doing CDC, it might be that you need a simpler solution in your project. Hibernate Envers is a Hibernate ORM extension… Read More
How to extract change data events from MySQL to Kafka using Debezium
Introduction As previously explained, CDC (Change Data Capture) is one of the best ways to interconnect an OLTP database system with other systems like Data Warehouse, Caches, Spark or Hadoop. Debezium is an open-source project developed by Red Hat which aims to simplify this process by allowing you to extract changes from various database systems (e.g. MySQL, PostgreSQL, MongoDB) and push them to Apache Kafka. In this article, we are going to see how you can extract events from MySQL binary logs using Debezium.
A beginner’s guide to CDC (Change Data Capture)
Introduction In this article, I’m going to explain what CDC (Change Data Capture) is, and why you should use it to extract database row-level changes. In OLTP (Online Transaction Processing) systems, data is accessed and changed concurrently by multiple transactions, and the database changes from one consistent state to another. An OLTP system always shows the latest state of our data, therefore facilitating the development of front-end applications that require near real-time data consistency guarantees. However, an OLTP system is no island, being just a small part of a larger system that… Read More