Databases supported for change tracking - Data Transmission Service

The change tracking feature of Data Transmission Service (DTS) captures real-time incremental data from your databases. You can use this data for various purposes, such as writing it to a destination system. This enables various use cases, including cache updates, asynchronous decoupling of business components, real-time synchronization between heterogeneous data sources, and complex ETL workflows.

Source database limitations

Limitation	Description
Network requirements	The network bandwidth must be 100 Mb/s or higher. The Round-Trip Time (RTT) between the source database and the DTS service must be less than 2 ms. A higher RTT degrades the performance of the change tracking task. For example, if a database in the Singapore region connects to DTS in the China (Hong Kong) region through a VPN, the long physical distance can cause a high RTT, leading to task latency.
Business requirements	The peak log volume must be less than 1 TB, with an average hourly log volume under 50 GB and peak traffic under 15 MB/s. Important By default, DTS pulls logs from the entire database instance. High-volume data changes in objects that are not part of the change tracking task can also cause task latency. Batch data updates or large-scale changes to large object (LOB) data types, such as CLOB, BLOB, or LONG, may cause task latency. To prevent this, run these operations in smaller batches or avoid them when possible. Avoid frequent DELETE or UPDATE operations on tables without a primary key to prevent task latency. To prevent task latency, execute no more than 10 DDL statements per second. Avoid large transactions. A single transaction that generates more than 100 GB of logs may cause the task to fail.

Change tracking plans

Note

Whether you can create a cross-account change tracking task depends on the source database type and access method. When configuring the task, you must set the Replicate Data Across Alibaba Cloud Accounts parameter to Yes for the source database. For more information, see Configure a cross-account DTS task.

Source database	Supported types	Documentation
self-managed MySQL Versions 5.1, 5.5, 5.6, 5.7, 8.0, and 8.4 ApsaraDB RDS for MySQL All versions	data update schema update	Track data changes from an ApsaraDB RDS for MySQL instance
PolarDB for MySQL All versions	data update schema update	Create a PolarDB for MySQL change tracking task
PolarDB-X 1.0 Important The underlying databases for PolarDB-X must be based on ApsaraDB RDS for MySQL. DTS does not support databases created on PolarDB for MySQL.	data update schema update	Create a PolarDB-X 1.0 change tracking task
PolarDB-X 2.0 Important The underlying databases for PolarDB-X must be based on ApsaraDB RDS for MySQL. DTS does not support databases created on PolarDB for MySQL.	data update schema update	Create a PolarDB-X 2.0 change tracking task
PolarDB for PostgreSQL (Compatible with Oracle) All versions	data update	Create a change tracking task for PolarDB for PostgreSQL (Compatible with Oracle)
self-managed Oracle (non-RAC architecture) Versions 9i, 10g, and 11g	data update schema update	Create an Oracle change tracking task
ApsaraDB RDS for PostgreSQL Versions 9.4, 10, 11, 12, 13, 14, 15, 16, 17, and 18 self-managed PostgreSQL Versions 9.4.8 and later, 9.5, 9.6, 10.x, 11.x, 12.x, 13.x, 14.x, 15.x, 16.x, 17.x, and 18.x	data update	Create an RDS PostgreSQL change tracking task
Data Management (DMS) logical database Important The logical database must consist of database shards from multiple PolarDB for MySQL instances.	data update	Create a DMS logical database change tracking task
PolarDB for PostgreSQL Versions 11, 14, 15, 16, 17, and 18	data update schema update	Create a change tracking task for PolarDB for PostgreSQL