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Debezium - Change Data Capture (CDC) Platform
A distributed platform for change data capture (CDC). Debezium streams row-level changes from databases to other systems, enabling real-time data integration, event sourcing, and data warehousing. Please log issues at https://issues.redhat.com/browse/DBZ.
Java
Added on 2025年6月7日11,472
Stars2,670
ForksJava
LanguageProject Introduction
Summary
Debezium is an open source distributed platform for change data capture. It turns your existing databases into event streams, allowing applications to react instantly to database changes.
Problem Solved
Integrating data across different systems or building event-driven architectures often requires polling databases for changes or relying on cumbersome trigger-based solutions. Debezium solves this by reliably capturing all committed database changes without modifying application code or requiring intrusive database schema changes.
Core Features
Real-time Change Streaming
Provides low-latency streaming of database changes, often within milliseconds of the transaction commit.
Multi-Database Support
Supports a wide range of databases including MySQL, PostgreSQL, MongoDB, SQL Server, Oracle, and more.
Kafka Integration
Integrates seamlessly with Apache Kafka and Kafka Connect, leveraging their scalability and reliability.
Tech Stack
Java
Apache Kafka
Apache Kafka Connect
Maven
Netty
Use Cases
Debezium can be applied in various scenarios where real-time access to database changes is crucial:
Real-time Data Synchronization
Details
Maintain up-to-date copies of data in search indexes (like Elasticsearch), caches (like Infinispan or Redis), or materialized views.
User Value
Ensures data consistency across systems with minimal latency.
Event Sourcing
Details
Build systems where all changes to application state are stored as a sequence of immutable events derived from database transactions.
User Value
Provides a robust audit trail and enables historical state reconstruction.
Streaming ETL/ELT
Details
Feed database changes directly into data warehouses or data lakes for near real-time analytical processing.
User Value
Accelerates the availability of fresh data for business intelligence and analytics.
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