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Change Data Capture

What is Apache Flink ?

Learn about Apache Flink, a distributed data processing engine for real-time analytics. Explore its features, use cases, and comparisons with other frameworks like Kafka and Spark.

Understanding Stream Processing: Real-Time Data Analysis and Use Cases

Learn about stream processing, its applications, challenges, and Alibaba Cloud's Realtime Compute for Apache Flink solution for real-time data analysis.

What is Change Data Capture (CDC)?

Change Data Capture (CDC) detects and captures data changes as they occur in source systems, such as databases or applications.

Converged Database Ecosystem: Building CDC Applications with EventBridge

This article introduces how to use EventBridge to build CDC applications from the aspects of CDC, CDC's application on EventBridge, and several best practice scenarios.

The New Features of MongoDB 6.0

This article reviews the history of MongoDB and explains the new features of MongoDB 6.0.

StarRocks x Flink CDC for End-to-End Real-Time Links

This article discusses real-time data warehouse construction and offers examples of using Flink CDC and StarRocks for real-time links and data updates.

An Interpretation of PolarDB-X Source Codes (3): CDC Code Structure

Part 3 of this 10-part series introduces the code engineering structure of GalaxyCDC and shows the construction process of the local development and debugging environment.

Flink CDC + OceanBase Data Integration Solution: Full Incremental Integration

This article introduces OceanBase and explains the application scenarios of Flink CDC and OceanBase.

Principle Analysis of Apache Flink CDC Batch and Stream Integration

This article focuses on the processing logic of Flink CDC.

Flink CDC Series – Part 5: Implement Real-Time Writing of MySQL Data to Apache Doris

Part 5 of this 5-part series explains how to use Flink CDC and Doris Flink Connector to monitor data from MySQL databases and store data in the tables in real-time.

Flink CDC Series – Part 4: Real-Time Extraction of Oracle Data, Demining, and Tuning Practices

Part 4 of this 5-part series shares the details of the Flink CDC version 2.1 trial process, including troubleshooting experiences and internal execution principles.

Flink CDC Series – Part 3: Synchronize MySQL Database and Table Shard to Build an Iceberg Real-Time Database

Part 3 of this 5-part series shows how to use Flink CDC to build a real-time database and handle database and table shard merge synchronization.

Flink CDC Series – Part 2: Flink MongoDB CDC Production Practices in XTransfer

Part 2 of this 5-part series explains how to realize Flink MongoDB CDC Connector through MongoDB Change Streams features based on Flink CDC.

Flink CDC Series – Part 1: How Flink CDC Simplifies Real-Time Data Ingestion

Part 1 of this 5-part series explains how to use Flink CDC to simplify the entry of real-time data into the database.

Use Flink Hudi to Build a Streaming Data Lake

This article introduces the optimization and evolution of Flink Hudi's original mini-batch-based incremental computing model through stream computing.

How to Analyze CDC Data in Iceberg Data Lake Using Flink

This article discusses the challenges and limitations of various solutions in CDC data analysis and describes how to use Flink and Iceberg to overcome them.

How Delta Lake and DLF Service Facilitate Real-time CDC Synchronization in a Data Lake

This article explains how to perform real-time CDC synchronization in a data lake using Alibaba Cloud's Data Lake Formation (DLF) service.