This topic describes how to migrate all data in an Oracle database to MaxCompute.

Background information

The database migration feature allows you to migrate all tables in an Oracle database to MaxCompute in an efficient and cost-effective manner. This saves the time and cost that are required to migrate your initial data to the cloud. For more information, see Rules and restrictions.


  1. Go to the Data Source page.
    1. Log on to the DataWorks console.
    2. In the left-side navigation pane, click Workspaces.
    3. In the top navigation bar, select the region where your workspace resides. Find the workspace and click Data Integration in the Actions column.
    4. In the left-side navigation pane of the page that appears, click Connection. The Data Source page appears.
  2. On the Data Source page, click New data source in the upper-right corner. In the Add data source dialog box, create an Oracle connection named clone_database for database migration. For more information, see Configure an Oracle data source.
  3. Click the Icon icon in the upper-left corner and choose All Products > Data Aggregation > Data Integration.
  4. On the Data Integration page, click Migrate Database in the left-side navigation pane.
  5. On the Migrate Database page, find the created Oracle connection and click Migration in the Operation column.
    The database migration settings page consists of three sections. Database migration
    No. Section Description
    1 Tables to migrate This section lists all the tables in the Oracle database that is connected based on the clone_database connection. You can select the tables to migrate based on your needs.
    2 Advanced settings You can configure the rules for converting the table names, field names, and data types between Oracle and MaxCompute.
    3 Basic settings You can specify whether to synchronize full or incremental data on a daily basis, whether to upload data in one or more batches, and the synchronization frequency and efficiency. You can also view the migration progress and results of each table after you commit sync nodes.
    If you select Synchronize Incremental Data Daily, you must specify the Incremental configuration mode parameter. Valid values:
    • Incremental field: Data Integration automatically generates a WHERE clause based on the specified field to read incremental data.
    • Where condition for incremental extraction?: Data Integration uses the WHERE clause that you specify to read incremental data.
  6. Click Advanced Settings. In the Advanced Settings dialog box, configure conversion rules based on your needs.
  7. Specify basic settings. In this example, set the following parameters:
    1. Set the Sync Method parameter to Synchronize Incremental Data Daily.
    2. Set the Incremental configuration mode parameter to Incremental field.
      Data Integration automatically generates a WHERE clause for each sync node to read incremental data based on the specified field and DataWorks scheduling parameters such as ${bdp.system.bizdate}.
    3. Set the Sync Mode parameter to Upload in Batches.
      You can set the Sync Mode parameter to Upload in Batches to protect the Oracle database from being overloaded.
    4. Configure Data Integration to start data synchronization for three tables every one hour from 00:00 each day.
    5. Select a resource group from the Resource Group drop-down list.
      You can select an exclusive resource group or a custom resource group for Data Integration. For more information, see Exclusive resource group for Data Integration and Create a custom resource group for Data Integration.
  8. Click Commit Sync Node. Then, you can view the migration progress and results of each table.
  9. Find Table a1 and click View Node to view the migration results.


After you complete the preceding steps, sync nodes are configured to migrate all data in the Oracle database to MaxCompute by using the clone_database connection. These sync nodes are run based on the specified schedule, daily by default. You can also create retroactive node instances to synchronize historical data.