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Data Management:Change tracking overview

Last Updated:Aug 26, 2026

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

  • Peak log volume: less than 1 TB. Average hourly log volume: less than 50 GB. Peak traffic: less than 15 MB/s.

    Important

    DTS pulls logs for the entire database instance by default. A high volume of changes to objects outside the migration scope can also cause task latency.

  • Avoid these patterns to prevent task latency or failure:

    • Batch updates or large-scale changes to LOB data types (CLOB, BLOB, LONG) — run these in smaller batches instead.

    • Frequent delete or update operations on tables without primary keys.

    • More than 10 DDL statements per second.

    • Single transactions that generate more than 100 GB of logs (causes task failure)

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