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Debezium

27 articles · Page 1 of 1
ITPUB
ITPUB
Sep 14, 2026 · Big Data

Flink CDC vs Canal: Building 99.99% Consistent Real-Time Data Pipelines

This article compares Flink CDC with traditional Canal-based architectures, explains Flink CDC's core principles including lock-free snapshots and exactly-once semantics, provides DataStream and SQL code examples for MySQL integration, and covers five high-frequency interview questions on DDL handling, DELETE capture, and large-table optimization.

Data LakeDebeziumExactly-Once
0 likes · 12 min read
Flink CDC vs Canal: Building 99.99% Consistent Real-Time Data Pipelines
Xiaolin Talks Programming
Xiaolin Talks Programming
Jul 16, 2026 · Backend Development

CDC + Outbox Pattern: Production-Grade Cross-Database Sync with Spring Boot & Kafka

This article details a production-ready cross-database synchronization architecture using CDC and Outbox pattern with Spring Boot, Debezium, and Kafka, covering schema design, connector configuration, transaction boundaries, ordering guarantees, idempotent consumption, dead-letter queues, and monitoring strategies.

CDCCross-Database SyncData Consistency
0 likes · 20 min read
CDC + Outbox Pattern: Production-Grade Cross-Database Sync with Spring Boot & Kafka
Big Data Technology Architecture
Big Data Technology Architecture
Mar 1, 2025 · Big Data

Core Principles and Practical Guide to Flink CDC

This article explains CDC fundamentals, details Flink CDC's architecture and advantages, provides setup steps, code examples for SQL and DataStream APIs, discusses performance tuning, consistency, common issues, and typical real‑time data integration scenarios.

CDCDebeziumFlink
0 likes · 7 min read
Core Principles and Practical Guide to Flink CDC
Java High-Performance Architecture
Java High-Performance Architecture
Sep 28, 2023 · Databases

How to Use Debezium for MySQL CDC in Spring Boot Without Adding Extra Middleware

Learn how to capture MySQL data changes using Debezium's CDC capabilities within a Spring Boot application, avoiding heavyweight message brokers by leveraging binlog monitoring, configuring connectors, handling snapshots, and processing change events for use cases like cache invalidation, data integration, and simplifying monolithic architectures.

CDCData IntegrationDebezium
0 likes · 24 min read
How to Use Debezium for MySQL CDC in Spring Boot Without Adding Extra Middleware
Java Interview Crash Guide
Java Interview Crash Guide
Aug 14, 2023 · Big Data

Unlocking Change Data Capture with Debezium in Spring Boot – No Extra Middleware Needed

This article explains how small web projects can avoid heavyweight message middleware by using CDC technology, specifically Debezium, to monitor MySQL binlog changes, outlines why Debezium outperforms alternatives like Canal, and provides step‑by‑step Spring Boot integration with configuration, code samples, and practical use‑case scenarios.

CDCDebeziumMySQL
0 likes · 22 min read
Unlocking Change Data Capture with Debezium in Spring Boot – No Extra Middleware Needed
IT Services Circle
IT Services Circle
Oct 26, 2022 · Databases

Debezium: Open‑Source Change Data Capture Platform – Overview, Architecture, Use Cases, and Installation Guide

This article introduces Debezium, an open‑source low‑latency change data capture platform that streams database row changes via Kafka, explains its architecture and common scenarios such as cache invalidation and CQRS, and provides step‑by‑step Docker commands to install ZooKeeper, Kafka, MySQL and the Debezium connector.

CDCData IntegrationDebezium
0 likes · 15 min read
Debezium: Open‑Source Change Data Capture Platform – Overview, Architecture, Use Cases, and Installation Guide
Big Data Technology Architecture
Big Data Technology Architecture
Oct 18, 2022 · Databases

Debezium 2.0.0.Final Release: New Features, Connector Enhancements, and Improvements

Debezium 2.0.0.Final introduces major enhancements such as Java 11 migration, improved incremental snapshot controls, multi‑partition support, new storage modules, pluggable topic naming, expanded connector capabilities for Cassandra, MongoDB, MySQL, Oracle, PostgreSQL and Vitess, plus ARM64 container images and community updates.

Database ConnectorsDebeziumIncremental Snapshot
0 likes · 28 min read
Debezium 2.0.0.Final Release: New Features, Connector Enhancements, and Improvements
Big Data Technology & Architecture
Big Data Technology & Architecture
Feb 16, 2022 · Big Data

Using Flink CDC to Capture MySQL Changes and Sync Them to ClickHouse

This article introduces Change Data Capture (CDC), compares query‑based and log‑based approaches, explains Debezium and ClickHouse, and provides detailed Flink CDC and Flink SQL CDC examples—including Java source code, custom deserialization schema, ClickHouse sink implementation, and required Maven dependencies—to synchronize MySQL data into ClickHouse in real time.

CDCClickHouseData Streaming
0 likes · 17 min read
Using Flink CDC to Capture MySQL Changes and Sync Them to ClickHouse
Big Data Technology & Architecture
Big Data Technology & Architecture
Dec 22, 2021 · Big Data

Using Flink CDC to Capture MySQL Changes and Sink Them into ClickHouse

This article explains Change Data Capture (CDC), compares query‑based and log‑based approaches, introduces Debezium and ClickHouse, and provides step‑by‑step Flink CDC and Flink SQL CDC examples—including Java source, deserialization, sink code and required Maven dependencies—to stream MySQL binlog changes into ClickHouse for real‑time analytics.

CDCClickHouseData Streaming
0 likes · 14 min read
Using Flink CDC to Capture MySQL Changes and Sink Them into ClickHouse
Big Data Technology & Architecture
Big Data Technology & Architecture
Nov 8, 2021 · Big Data

Understanding Flink CDC 2.0: Core Design, Snapshot & Incremental Reading, and Code Walkthrough

This article introduces Flink CDC 2.0, explains its distributed full‑load and incremental reading mechanisms, details the slice partitioning, snapshot correction, and binlog handling logic, and provides a complete Java example that demonstrates how to configure Flink SQL, MySQL source, and Kafka sink.

CDCData IntegrationDebezium
0 likes · 29 min read
Understanding Flink CDC 2.0: Core Design, Snapshot & Incremental Reading, and Code Walkthrough
Architect
Architect
Oct 6, 2021 · Big Data

Design and Implementation of a Real-time and Offline Integrated Query System

This article details the requirements, architecture, and implementation of a real-time and offline integrated query system, covering data ingestion via Debezium and Confluent Platform, storage in Kudu and HDFS, query engines Presto and Kylin, and strategies for data synchronization, partitioning, and scaling.

DebeziumKafkaKudu
0 likes · 19 min read
Design and Implementation of a Real-time and Offline Integrated Query System
Big Data Technology Architecture
Big Data Technology Architecture
Aug 17, 2021 · Big Data

Detailed Overview of Flink CDC 2.0: Architecture, Features, and Future Roadmap

This article provides an in‑depth technical overview of Flink CDC 2.0, covering its CDC fundamentals, comparison of query‑based and log‑based approaches, the new lock‑free chunk algorithm, FLIP‑27 based parallel snapshot reading, performance benchmarks, documentation improvements, and future roadmap for stability and ecosystem integration.

Data IntegrationDebeziumFlink CDC
0 likes · 16 min read
Detailed Overview of Flink CDC 2.0: Architecture, Features, and Future Roadmap
Big Data Technology & Architecture
Big Data Technology & Architecture
Jul 20, 2021 · Big Data

Common Issues and Solutions for Flink CDC with MySQL

This article summarizes frequent problems encountered when using Flink CDC with MySQL—including Kafka version conflicts, checkpoint timeouts, permission errors, global lock issues, and DDL parsing failures—and provides practical configuration tweaks and code examples to resolve them.

CDCCheckpointDebezium
0 likes · 11 min read
Common Issues and Solutions for Flink CDC with MySQL
Programmer DD
Programmer DD
Jun 14, 2021 · Databases

Master Real‑Time Change Data Capture with Debezium and Spring Boot

Learn how to capture and stream real‑time database changes using Debezium’s distributed CDC framework, configure MySQL binlog, integrate the embedded engine with Spring Boot, and process change events with sample code and Docker setup for robust data pipelines.

CDCDebeziumKafka
0 likes · 11 min read
Master Real‑Time Change Data Capture with Debezium and Spring Boot
Beike Product & Technology
Beike Product & Technology
Dec 10, 2020 · Big Data

Overview and Practical Guide to Debezium MongoDB Source Connector

This article explains how Debezium's MongoDB Source Connector captures change events from replica sets or sharded clusters, streams them to Kafka topics, and provides detailed configuration, deployment, monitoring, and troubleshooting steps for building reliable change‑data‑capture pipelines.

ConnectorDebeziumKafka Connect
0 likes · 11 min read
Overview and Practical Guide to Debezium MongoDB Source Connector
dbaplus Community
dbaplus Community
Sep 1, 2020 · Big Data

Mastering Real‑Time MySQL Binlog Sync with Debezium, Kafka & Hive

This article presents a systematic guide to real‑time MySQL binlog ingestion, outlining three core principles—decoupling from business data, handling schema changes, and ensuring traceability—followed by concrete Debezium‑Kafka‑Hive solutions, scenario‑specific tactics, and practical tips for reliable data pipelines.

Data IngestionDebeziumHive
0 likes · 15 min read
Mastering Real‑Time MySQL Binlog Sync with Debezium, Kafka & Hive
Architects Research Society
Architects Research Society
Aug 31, 2020 · Databases

What Is Debezium? Overview, Architecture, and Features

Debezium is an open‑source distributed platform built on Apache Kafka that captures row‑level changes from databases via change data capture, providing source connectors, an optional embedded engine, and features like low‑latency streaming, snapshots, filtering, masking, and integration with various sink systems.

CDCDatabase StreamingDebezium
0 likes · 8 min read
What Is Debezium? Overview, Architecture, and Features
Architects Research Society
Architects Research Society
Oct 13, 2019 · Databases

What is Debezium? Overview, Architecture, and Features

Debezium is an open‑source distributed platform built on Apache Kafka that turns existing databases into real‑time event streams by capturing row‑level changes via change data capture, offering source and embedded connectors, flexible topic routing, and features such as snapshots, filtering, masking, and monitoring.

CDCDebeziumKafka Connect
0 likes · 7 min read
What is Debezium? Overview, Architecture, and Features