Change Data Capture (CDC) with PostgreSQL and Debezium

Change Data Capture (CDC) has revolutionized the way we interact with data, enabling real-time tracking and propagation of changes within databases. In this blog post, we'll delve into harnessing the power of CDC using two formidable tools: PostgreSQL and Debezium.

Introduction

Change Data Capture (CDC) is the backbone of modern data architectures, allowing seamless tracking and delivery of database changes to downstream systems. PostgreSQL, revered for its extensibility and SQL compliance, serves as our foundation for data storage. Complementing it is Debezium, a versatile open-source platform dedicated to change data capture.

Minimum Software Requirements

To embark on this journey, ensure you have Docker installed, facilitating the effortless setup of PostgreSQL, Zookeeper, Kafka, Debezium, and schema-registry components. Docker Compose streamlines the orchestration of these services, ensuring a hassle-free setup process.

Getting Started

Setup

To kickstart our CDC adventure, we utilize a Docker Compose configuration, encapsulating the required services. This configuration, detailed in the provided docker-compose.yaml file, lays the groundwork for our PostgreSQL and Debezium setup.

DB Configuration

In PostgreSQL, we define a STUDENT table with essential columns, setting the stage for our CDC operations. Leveraging PostgreSQL's robust functionality, we configure the STUDENT table with full REPLICA IDENTITY, ensuring comprehensive change tracking.

CREATE TABLE STUDENT(id INTEGER PRIMARY KEY, name VARCHAR);

ALTER TABLE public.student REPLICA IDENTITY FULL;

SELECT * FROM STUDENT;

Setup debezium Connector

Debezium seamlessly integrates with PostgreSQL via a dedicated connector. With the provided script, debezium-postgresql-connector.sh, we initiate and configure the connector, enabling seamless communication between our database and Debezium.

Tail kafka CDC topic

Monitoring the CDC topic in Kafka provides real-time insights into database changes. By tailing the Kafka CDC topic, as illustrated in tail_cdc_kafka_topic.sh, we gain immediate visibility into data modifications, empowering us to track changes effectively.

Add, Update, Delete Records

To witness CDC in action, we simulate data modifications within our PostgreSQL database. By executing SQL statements to add, update, and delete records in the STUDENT table, we trigger CDC events that are seamlessly propagated to the Kafka CDC topic.

-- Add records
INSERT INTO STUDENT(id,name) VALUES (1,'JOHN');
INSERT INTO STUDENT(id,name) VALUES (2,'JANE');

-- Update record
UPDATE STUDENT SET name='JOHNNY' WHERE ID=1;

In conclusion, the synergy between PostgreSQL and Debezium unlocks unparalleled capabilities in Change Data Capture, revolutionizing how we perceive and interact with real-time data changes. Through meticulous setup and intuitive configuration, harnessing CDC becomes not just a possibility but a powerful reality, propelling data-driven decision-making to new heights.