beryllw commented on code in PR #3347:
URL: https://github.com/apache/fluss/pull/3347#discussion_r3300764320


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website/docs/engine-flink/flink-cdc-integration.md:
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+---
+sidebar_label: Flink CDC
+title: Flink CDC Integration
+sidebar_position: 9
+---
+
+# Flink CDC Integration
+
+[Flink CDC](https://nightlies.apache.org/flink/flink-cdc-docs-master/) is a 
streaming data integration tool built on top of Apache Flink that can capture 
real-time changes from various databases. Flink CDC supports Fluss as a 
[Pipeline Sink 
Connector](https://nightlies.apache.org/flink/flink-cdc-docs-master/docs/connectors/pipeline-connectors/fluss/),
 making it straightforward to sync CDC data from databases like PostgreSQL, 
MySQL, and Oracle into Fluss.
+
+There are two ways to sync database changes into Fluss using Flink CDC:
+
+- **Flink SQL with CDC connectors** — Use SQL to define CDC source tables and 
write data into Fluss tables. Best for per-table synchronization with 
SQL-native workflows.
+- **Flink CDC Pipeline Connector** — Use a YAML pipeline definition to sync 
entire databases (including multiple tables) into Fluss. Best for 
whole-database synchronization.
+
+## Prerequisites
+
+- A running **Fluss cluster** (CoordinatorServer + TabletServer). See 
[Deploying with Docker](../install-deploy/deploying-with-docker.md) for setup 
instructions.
+- A running **Flink cluster** with the required connector JARs. See [Getting 
Started with Flink](getting-started.md) for Flink setup.
+- The required connector JARs placed under `<FLINK_HOME>/lib/`. The examples 
below use MySQL as the source, but other databases (PostgreSQL, Oracle, etc.) 
are also supported — see [Further Reading](#further-reading) for the full list 
of connectors.

Review Comment:
   Would it make sense to use PostgreSQL as the source example instead of 
MySQL? The original issue (#1939) describes the use case with PostgreSQL, and 
it's more widely adopted internationally, which might resonate better with 
readers.



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