This topic provides reference performance data for replication workloads in data migration mode. It describes actual performance tests and lists the results of the tests.


The performance data provided in this document should only be used for reference when you plan the capacity of your replication workloads. The data in this document are not guaranteed performance levels and the actual performance of your migration tasks may differ from the data provided. For performance levels guaranteed by DTS, see the Service Level Agreement (SLA).

Test method

In this test, we created an incremental migration task between two ApsaraDB RDS for MySQL instances. Then, we performed a stress test that made highly frequent updates to the source ApsaraDB RDS for MySQL instance and viewed the performance metrics of the data migration task.

Table 1. Database configurations
Instance RDS instance configuration Maximum performance
Source instance
  • Instance type: rds.mys2.8xlarge
  • Memory: 48,000 MB
  • Maximum connections: 2,000
  • Maximum QPS: 18,000
  • Maximum IOPS: 14,000
Target instance
  • Instance type: rds.mys2.8xlarge
  • Memory: 48,000 MB
  • Maximum connections: 2,000
  • Maximum QPS: 18,000
  • Maximum IOPS: 14,000
  • The number of test tables is 20.
  • Each test table has a primary key.
  • The size of each record is 1 KB.
  • Each transaction has an average of two DML operations and one COMMIT operation. The ratio of INSERT, UPDATE, and DELETE operations is 3:1:2.
  • If an SQL statement operates on multiple rows, Data Transmission Service (DTS) identifies the operation as multiple data updates. If you perform INSERT, UPDATE, and DELETE operations on a data record multiple times, DTS also identifies the operations as multiple data updates.
  • DTS identifies each COMMIT operation as a data update.

Test results

Source instance region Target instance region Network latency between instances (milliseconds) Instance size TPS QPS
China (Hangzhou) China (Hangzhou) 0.26 small 2,566 8,981
China (Hangzhou) China (Hangzhou) 0.26 medium 4,726 16,541
China (Hangzhou) China (Hangzhou) 0.26 large 6,378 23,204
China (Hangzhou) China (Qingdao) 26 small 2,469 8,641
China (Hangzhou) China (Qingdao) 26 medium 4,856 16,996
China (Hangzhou) China (Qingdao) 26 large 5,439 20,400
China (Hangzhou) China (Beijing) 26 small 2,533 8,866
China (Hangzhou) China (Beijing) 26 medium 5,038 17,633
China (Hangzhou) China (Beijing) 26 large 6,829 26,100
China (Hangzhou) US (Silicon Valley) 175 small 1,753 6,135
China (Hangzhou) US (Silicon Valley) 175 medium 2,837 9,929
China (Hangzhou) US (Silicon Valley) 175 large 3,884 15,500
Singapore US (Silicon Valley) 198 small 1,104 4,000
Singapore US (Silicon Valley) 198 medium 1,724 6,334
Singapore US (Silicon Valley) 198 large 2,256 8,300
Note These test results indicate the maximum performance of data migration tasks that are configured with different instance sizes. Many other factors may affect the performance of incremental data migration. For example, the performance is reduced if the table to be migrated does not have a primary key, if the network latency is high, or if the source and target database servers operate at low performance.