This topic describes the terms that are used in the Data Transmission Service (DTS) documentation.
| Term | Description |
| Precheck | The operation that the system performs before it performs a data migration, data synchronization, or change tracking task. For example, the following items are checked: the connectivity between DTS servers and the source and destination databases, database account permissions, binary log settings, and database versions. For more information, see Source database connectivity. Note If a task fails to pass the precheck, you can click the  icon next to each failed item to view the details. After you troubleshoot the issues based on the causes, run a precheck again. |
| Schema migration | The data migration phase during which DTS migrates the schemas of objects, such as tables, views, triggers, and stored procedures, from the source database to the destination database. To migrate the schemas of objects between heterogeneous databases, DTS converts the schemas of the objects in the source database into schemas that are supported by the destination database. For example, DTS can convert data of the NUMBER data type in Oracle databases to data of the DECIMAL data type in MySQL databases. |
| Full data migration | The data migration phase during which DTS migrates historical data from the source database to the destination database. If you select only schema migration and full data migration as the migration types, DTS does not migrate incremental data generated in the source database. To ensure data consistency, do not write data to the source database during data migration. Note
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| Incremental data migration | The data migration phase during which DTS continuously synchronizes ongoing changes from the source database to the destination database. Data changes made during the full data migration phase are migrated to the destination database. This minimizes the service downtime. Note Incremental data migration is a continuous real-time process. To stop this process, you must manually stop the data migration task. |
| Initial synchronization | The initial synchronization phase during which DTS collects incremental data and then synchronizes the schemas and historical data of objects from the source database to the destination database. This happens before DTS starts to synchronize incremental data. Initial synchronization includes incremental data collection, initial schema synchronization, and initial full data synchronization.
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| Synchronization performance | A measurement based on the number of data records that are synchronized to the destination database per second. Unit: records per second (RPS). For more information, see Instance classes of data synchronization instances. |
| Synchronization latency | A measurement based on the difference between the timestamp of the latest data record synchronized to the destination database and the current timestamp of the source database. If the synchronization latency is zero, the destination database is in sync with the source database. |
| Data updates | The operations that are performed to modify data without modifying schemas, such as the INSERT, DELETE, and UPDATE operations. |
| Schema updates | The operations that are performed to modify schema syntax, such as the CREATE TABLE, ALTER TABLE, and DROP VIEW operations. |
| Timestamp range | The timestamp range of the incremental data that is stored in a change tracking task. By default, a change tracking task retains the data that is generated in the last 24 hours. DTS regularly deletes expired incremental data and updates the timestamp range of change tracking tasks. Note The timestamp of incremental data is generated when the data is updated in the source database and written to the transaction log. |
| Consumption checkpoint | The timestamp of the latest incremental data record that is consumed by a client. Each time the client consumes a data record, it returns a confirmation message to DTS. DTS updates and saves the consumption checkpoint. If the client stops responding, DTS automatically resumes data from the last consumption checkpoint and pushes the data to another consumer. |