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🚀 Building a Custom Change Data Capture (CDC) System Using Arbitrary Tables
A comprehensive guide to implementing a custom Change Data Capture (CDC) system using arbitrary tables, providing complete control and flexibility over data change tracking. The article includes pract
ical PostgreSQL examples for tracking user table modifications, along with detailed implementation steps and considerations for when to use this approach.

Reasons to Read -- Learn:

  • how to implement a flexible, database-agnostic CDC system without relying on specialized tools or database-specific features, complete with working PostgreSQL code examples.
  • how to create a custom logging system that captures additional metadata like user IDs and IP addresses alongside data changes, enabling better audit trails and system integration.
  • practical SQL procedures and application logic for tracking INSERT, UPDATE, and DELETE operations, with detailed examples using JSONB data types for storing change history.
  • publisher: @priyanshu011109
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