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Feature Overview

The data sync feature refers to real-time data sync between two database sources. It is suitable for cloud-local active-active, multi-site active-active, and cross-border data sync as well as real-time data warehousing.

Unlike data migration which is a one-time short-term task to migrate the entire database, data sync is a continuous task. After a task is created, the data will be continuously synced (almost in real time) to keep consistency between the source and target databases.

How to Implement

The following takes MySQL sync as an example to describe the data sync feature, where data is exported from the source database and imported into the target database, and key steps include structure initialization, full data initialization, and incremental data processing.

• Structure initialization
  Structure initialization is to create the same table structure information in the target database as that in the source database. When configuring a sync task, you can select whether to sync the table structure. If the target database already contains the same structural information, you simply need to sync the data; otherwise, you'll need to sync the information as well.

• Full data initialization
  After structure initialization is completed, DTS will initialize the existing data, i.e., exporting all existing data from the source database and import it into the target database.

• Incremental data processing
  In incremental data processing, DTS gets the incremental data continuously through the source database's binlog and persistently stores such data in the intermediate storage after a series filtering and conversion operations. After importing the full data, it continuously replays the changed incremental data stored in the intermediate storage into the target database in order to ensure data consistency between the source and target databases.

Supported Topologies

The basic unit of the sync service is one-way sync. During configuration, you can choose to use data definition language (DDL) or data manipulation language (DML) for sync. By combining one-way sync tasks, you can customize various complex topologies.
In a complex topology, technical measures will be used for DML operations to avoid data loop. However, for DDL, the data sync service will check for loop during configuration to avoid forming DDL loop.

Below are some common topologies, which you can customize by purchasing multiple sync instances:

• One-to-One one-way sync

  

• Cascaded one-way sync

  

• One-to-Many one-way sync

  

• Many-to-One one-way sync

  

• Two-Way sync

  

• Cascaded two-way sync
  

  

Typical Use Cases

By using DTS, you can sync data between MySQL databases in multiple regions to implement multi-site active-active deployment. Database instances in each region can run in the cloud or your self-built IDC.

Restrictions

You can implement two-way sync by combining one-way sync tasks, but the following restrictions exist:

• Your business should cooperate in terms of data consistency, i.e., ensuring that data with the same primary key is updated only on the same node.
• If a data sync conflict occurs, DTS will process the data strictly according to the selected conflict processing policy. You need to confirm whether the corresponding policy meets your business expectation during configuration.
• DML statements support two-way sync, but DDL statements support only one-way sync. To create two-way sync, ensure that DDL sync is disabled in one of the one-way instances.

Supported Database Types

For more information on the source and target database types, versions, and sync types supported for data sync, see Databases Supported for Data Sync.

Supported Advanced Features