Building an App with Change Data Capture (CDC) Tool

Introduction

In today's modern applications, the need to track changes in real-time data is crucial for a variety of use cases, including analytics, real-time processing, and system integration. One of the most efficient ways to achieve this is by implementing Change Data Capture (CDC).

This article explores how to build an application that leverages a CDC tool, such as Debezium, to track changes in a database, capture them in real-time, and forward those changes to a messaging system like Apache Kafka for processing. We'll walk through the process and architecture of using CDC to build an event-driven app.

What is Change Data Capture (CDC)?

Change Data Capture (CDC) is a technique used to identify and capture changes made to a database, such as INSERT, UPDATE, and DELETE operations. CDC allows applications to react to changes in the data layer in real-time without the need for constant polling or complex queries.

Debezium is one of the most popular open-source CDC tools. It captures changes from databases like MySQL, PostgreSQL, and others, and streams those changes into Apache Kafka topics.

Components of the Architecture

Before diving into the implementation, let's break down the architecture components:

Database:

• The data source where your app stores information. Common databases used in this architecture include MySQL, PostgreSQL, etc.
• Changes to the data (like INSERT, UPDATE, DELETE) are captured by the CDC tool.

CDC Tool (Debezium):

• Debezium listens to the database's changes (using the binlog for MySQL, for example) and captures them as events.
• It then publishes those events to an Apache Kafka topic, making them available for other services to consume.

Kafka:

• Apache Kafka acts as the message broker that stores and streams these data changes in topics.
• Kafka ensures that data changes are available to multiple consumers without creating tight coupling between your database and consumers.

Consumer (App or API):

• A consumer application subscribes to the Kafka topic and processes the data.
• The consumer can perform tasks like transforming the data, storing it in a different database (NoSQL), triggering notifications, or performing additional business logic.

NoSQL Database:

• In some use cases, the consumer might store the processed changes in a NoSQL database like MongoDB or Elasticsearch, where the data can be queried and analyzed efficiently.

Architecture

Here's an overview of the components and how they interact:

Step-by-Step Process

1. Set up your Database:
   • For this example, let's assume we are using MySQL. Set up a MySQL database where your application stores the data.
2. Configure Debezium:
   • Install and configure Debezium to monitor the MySQL database. You'll need to configure the binlog in MySQL and ensure that Debezium is connected to your Kafka instance.
3. Kafka Configuration:
   • Set up Kafka to handle the messages that Debezium produces. Create topics where the CDC events will be published.
4. Create Consumers:

• Develop a Kafka consumer that listens to the Kafka topics where Debezium sends the events. This consumer processes the data (e.g., transforming the data or storing it in a NoSQL database).

1. Persist to NoSQL:
   • If needed, the consumer stores the processed data in a NoSQL database (like MongoDB or Elasticsearch) for further analysis or querying.

Results

• Github:
  https://github.com/JhonnyARM/ArticuloU3

• Docker Compose

• Swagger Logs & Products endpoints

Benefits of Using CDC in Your Application

• Real-Time Data Processing: CDC enables your app to react to changes as they happen, providing real-time insights and updates.
• Scalability: By using Kafka as a message broker, you can scale your architecture horizontally, adding more consumers as needed.
• Decoupling: The CDC tool and Kafka decouple your database from the rest of your application. This reduces the risk of bottlenecks and allows for more efficient data handling.
• Flexibility: Storing the data in a NoSQL database after processing allows for more flexible querying and faster access to the data.

Conclusion

Building an app with a Change Data Capture (CDC) tool like Debezium enables your application to react to database changes in real-time. By integrating Debezium with Apache Kafka and NoSQL databases, you can implement an efficient, scalable, and flexible architecture that handles large volumes of data changes with minimal latency.