Change Data Capture (CDC) is a powerful feature in SQL Server that enables real-time data integration by tracking INSERT, UPDATE, and DELETE operations on tables. In this article, we’ll explore how SQL Server CDC works, and how to integrate it seamlessly with Apache SeaTunnel to build efficient, scalable data pipelines for AI-ready systems.
🔍 What is CDC?
Change Data Capture (CDC) is a mechanism that logs changes in SQL Server tables by writing them to system-managed change tables. It captures:
INSERTUPDATEDELETE
Compared to traditional polling or trigger-based solutions, CDC offers:
✅ Non-intrusive design (no schema changes)
✅ Low-latency change tracking
✅ Easy downstream integration with Kafka, SeaTunnel, ETL tools
🧠 How CDC Works: Architecture Overview
🔧 Key Components
| Component | Description |
|---|---|
cdc.dbo_customer_CT |
Change table storing captured modifications |
| Capture Job | SQL Agent job that scans the transaction log and parses changes |
| Cleanup Job | Cleans up old CDC data periodically |
| LSN (Log Sequence Number) | Log marker for each change, supports resume capability |
⚙️ How to Enable CDC in SQL Server
-- Enable CDC for the database
EXEC sys.sp_cdc_enable_db;
-- Enable CDC for a specific table
EXEC sys.sp_cdc_enable_table
@source_schema = N'dbo',
@source_name = N'customer',
@role_name = NULL,
@supports_net_changes = 0;
After enabling, SQL Server auto-generates:
-
cdc.change_tables: One per source table -
cdc.lsn_time_mapping: Timestamp mapping - SQL Agent jobs:
cdc.<DBName>_captureandcdc.<DBName>_cleanup
🔗 SeaTunnel Integration with SQL Server CDC
Apache SeaTunnel supports CDC natively through its CDC connector. Here’s a sample configuration:
source {
SqlServer-CDC {
plugin_output = "customers"
username = "sa"
password = "Y.sa123456"
startup.mode = "initial"
database-names = ["column_type_test"]
table-names = ["column_type_test.dbo.full_types"]
base-url = "jdbc:sqlserver://localhost:1433;databaseName=column_type_test"
}
}
SeaTunnel reads from the CDC table and transforms change events into a unified format for downstream processing.
🧾 Example CDC Table Structure
Querying the change table after CDC is enabled:
SELECT * FROM cdc.dbo_customer_CT;
You’ll see fields like:
| Field | Description |
|---|---|
__$start_lsn |
Log sequence number where change began |
__$operation |
Operation type (1 = DELETE, 2 = INSERT, 3/4 = UPDATE) |
__$seqval |
Sequence value for ordering |
| Table columns | Snapshot of the row’s data before/after the change |
📊 Comparison: CDC vs Trigger vs Timestamp Polling
| Feature | CDC | Trigger | Timestamp Polling |
|---|---|---|---|
| Intrusiveness | None | High | None |
| Latency | Medium (seconds) | Low (milliseconds) | High (minutes) |
| Resource Overhead | Medium | High | Medium |
| Delete Detection | ✅ | ✅ | ❌ |
| SeaTunnel Compatibility | ✅ | ❌ | ✅ |
⚠️ Important Tips
- SQL Server Agent must be enabled
- Create a dedicated read-only CDC user for best practices
- Adjust cleanup retention (default: 3 days):
EXEC sys.sp_cdc_change_job
@job_type = 'cleanup',
@retention = 43200 -- 30 days (in minutes)
✅ Conclusion
SQL Server’s CDC mechanism offers a reliable, cost-effective way to track data changes. When paired with Apache SeaTunnel’s real-time data ingestion capabilities, it becomes a powerful combo for building AI-ready data lakes, real-time analytics pipelines, and cross-database synchronization solutions.
📌 Want to deploy SeaTunnel + SQL Server CDC in production?
Contact our team for deployment guides, production tuning tips, and case studies: service@whaleops.com
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