[docs]:Add Flink CDC integration doc under Flink

website/docs/engine-flink/flink-cdc-integration.md

@@ -0,0 +1,212 @@
+---
+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.
+  - For SQL approach: [flink-sql-connector-mysql-cdc](https://mvnrepository.com/artifact/org.apache.flink/flink-sql-connector-mysql-cdc) and the [Fluss Flink connector](getting-started.md)
+  - For Pipeline approach: [flink-cdc-pipeline-connector-fluss](https://mvnrepository.com/artifact/org.apache.flink/flink-cdc-pipeline-connector-fluss)
+
+## Example 1: Sync MySQL to Fluss with Flink SQL
+
+This example shows how to capture changes from a MySQL table and write them into a Fluss primary-key table using Flink SQL.
+
+### Step 1: Start MySQL with Docker
+
+Start a MySQL instance with binlog enabled using the Debezium example image:
+
+```shell
+docker run -d --name mysql \
+  -e MYSQL_ROOT_PASSWORD=123456 \
+  -e MYSQL_USER=mysqluser \
+  -e MYSQL_PASSWORD=mysqlpw \
+  -p 3306:3306 \
+  debezium/example-mysql:1.1
+```
+
+Wait for the container to start, then connect to MySQL:
+
+```shell
+docker exec -it mysql mysql -uroot -p123456
+```
+
+Create a sample database and table:
+
+```sql
+CREATE DATABASE mydb;
+USE mydb;
+CREATE TABLE orders (
+  order_id INT AUTO_INCREMENT PRIMARY KEY,
+  customer_name VARCHAR(255),
+  product VARCHAR(255),
+  quantity INT,
+  order_date TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+);
+
+INSERT INTO orders (customer_name, product, quantity) VALUES
+  ('Alice', 'Laptop', 1),
+  ('Bob', 'Phone', 2),
+  ('Charlie', 'Tablet', 3);
+```
+
+### Step 2: Create a MySQL CDC Source Table in Flink SQL
+
+Open the Flink SQL CLI and create a CDC source table that captures changes from the MySQL `orders` table:
+
+```sql title="Flink SQL"
+CREATE TABLE mysql_orders (
+  order_id INT,
+  customer_name STRING,
+  product STRING,
+  quantity INT,
+  order_date TIMESTAMP(3),
+  PRIMARY KEY (order_id) NOT ENFORCED
+) WITH (
+  'connector' = 'mysql-cdc',
+  'hostname' = 'localhost',
+  'port' = '3306',
+  'username' = 'root',
+  'password' = '123456',
+  'database-name' = 'mydb',
+  'table-name' = 'orders'
+);
+```
+
+### Step 3: Create a Fluss Sink Table
+
+Create a Fluss Catalog and a primary-key table in Fluss to receive the CDC data:
+
+```sql title="Flink SQL"
+CREATE CATALOG fluss_catalog WITH (
+  'type' = 'fluss',
+  'bootstrap.servers' = 'localhost:9123'
+);
+
+USE CATALOG fluss_catalog;
+
+CREATE DATABASE IF NOT EXISTS mydb;
+
+CREATE TABLE mydb.orders (
+  order_id INT,
+  customer_name STRING,
+  product STRING,
+  quantity INT,
+  order_date TIMESTAMP(3),
+  PRIMARY KEY (order_id) NOT ENFORCED
+);
+```
+
+### Step 4: Sync Data
+
+Switch back to the default catalog and start the synchronization job:
+
+```sql title="Flink SQL"
+USE CATALOG default_catalog;
+
+INSERT INTO fluss_catalog.mydb.orders
+SELECT * FROM mysql_orders;
+```
+
+This starts a streaming job that continuously captures changes from MySQL and writes them to Fluss.
+
+### Step 5: Query the Data in Fluss
+
+You can now query the synced data in Fluss:
+
+```sql title="Flink SQL"
+-- Switch to Fluss catalog
+USE CATALOG fluss_catalog;
+
+-- Point query by primary key
+SELECT * FROM mydb.orders WHERE order_id = 1;
+
+-- Streaming read to observe real-time changes
+SELECT * FROM mydb.orders;
+```
+
+Try inserting or updating rows in MySQL — changes will be captured and reflected in Fluss in real time. Open a MySQL client:
+
+```shell
+docker exec -it mysql mysql -uroot -p123456 mydb
+```
+
+Then execute:
+
+```sql
+INSERT INTO orders (customer_name, product, quantity) VALUES ('Dave', 'Monitor', 2);
+UPDATE orders SET quantity = 5 WHERE customer_name = 'Alice';
+```
+
+## Example 2: Sync MySQL to Fluss with Pipeline Connector
+
+For whole-database synchronization, the Flink CDC Pipeline Connector allows you to define a YAML pipeline that syncs all tables from a MySQL database into Fluss automatically — without writing any SQL.
+
+:::note
+This example reuses the MySQL container started in [Example 1](#example-1-sync-mysql-to-fluss-with-flink-sql). If you haven't started it yet, follow [Step 1](#step-1-start-mysql-with-docker) first.
+:::
+
+### Step 1: Define the Pipeline YAML
+
+Create a file named `mysql-to-fluss.yaml`:
+
+```yaml
+source:
+  type: mysql
+  name: MySQL Source
+  hostname: 127.0.0.1
+  port: 3306
+  username: root
+  password: 123456
+  tables: mydb.\.*
+  server-id: 5401-5404
+
+sink:
+  type: fluss
+  name: Fluss Sink
+  bootstrap.servers: localhost:9123
+
+pipeline:
+  name: MySQL to Fluss Pipeline
+  parallelism: 2
+```
+
+### Step 2: Submit the Pipeline
+
+Submit the pipeline using the Flink CDC CLI:
+
+```shell
+./bin/flink-cdc.sh mysql-to-fluss.yaml
+```
+
+This will automatically create the corresponding tables in Fluss and start syncing data from all matching MySQL tables.
+
+For the full list of Pipeline Connector options, see the [Fluss Pipeline Connector Documentation](https://nightlies.apache.org/flink/flink-cdc-docs-master/docs/connectors/pipeline-connectors/fluss/).
+
+## Clean Up
+
+After finishing the examples, stop and remove the MySQL container:
+
+```shell
+docker stop mysql && docker rm mysql
+```
+
+## Further Reading
+
+- [Flink CDC Official Documentation](https://nightlies.apache.org/flink/flink-cdc-docs-master/)
+- [Flink CDC Pipeline Connectors Overview](https://nightlies.apache.org/flink/flink-cdc-docs-master/docs/connectors/pipeline-connectors/overview/)
+- [Flink SQL CDC Source Connectors](https://nightlies.apache.org/flink/flink-cdc-docs-master/docs/connectors/flink-sources/overview/)
+- [Fluss Flink Engine Options](options.md)

website/docs/quickstart/flink.md

@@ -508,4 +508,4 @@ docker compose down -v
 to stop all containers.
 
 ## Learn more
-Now that you're up and running with Fluss and Flink, check out the [Apache Flink Engine](engine-flink/getting-started.md) docs to learn more features with Flink or [this guide](/maintenance/observability/quickstart.md) to learn how to set up an observability stack for Fluss and Flink.
+Now that you're up and running with Fluss and Flink, check out the [Apache Flink Engine](engine-flink/getting-started.md) docs to learn more features with Flink, [Flink CDC Integration](engine-flink/flink-cdc-integration.md) to sync database changes into Fluss, or [this guide](/maintenance/observability/quickstart.md) to learn how to set up an observability stack for Fluss and Flink.