| Limits on the source database |
- Bandwidth requirements: The server to which the source database belongs must have
a sufficient egress bandwidth. Otherwise, the data synchronization speed is affected.
- The collections to be synchronized must have PRIMARY KEY or UNIQUE constraints and
all fields must be unique. Otherwise, the destination database may contain duplicate
data records.
- If you select collections as the objects to synchronize and you want to edit collections
(such as renaming collections), up to 1,000 collections can be synchronized in a single
data synchronization task. If you run a task to synchronize more than 1,000 collections,
a request error occurs. In this case, we recommend that you split the collections
to synchronize, configure multiple tasks to synchronize the tables, or configure a
task to synchronize the entire database.
- The following requirements must be met:
- The oplog feature must be enabled.
-
For an incremental data synchronization task, the oplogs of the source database must
be stored for more than 24 hours. If you perform both full data synchronization and
incremental data synchronization, the oplogs of the source database must be stored
for at least 7 days. After the full data synchronization is complete, you can set
the retention period to more than 24 hours. Otherwise, Data Transmission Service (DTS)
may fail to obtain the oplogs and the task may fail. In exceptional circumstances,
data inconsistency or loss may occur. Make sure that you set the retention period
of oplogs in accordance with the preceding requirements. Otherwise, the Service Level
Agreement (SLA) of DTS does not ensure service reliability and performance
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| Other limits |
- To ensure compatibility, the version of the destination MongoDB database must be the
same as or later than the version of the source MongoDB database. If the version of
the destination database is earlier than the version of the source database, database
compatibility issues may occur.
- DTS cannot synchronize data from the admin or local database.
- Transaction information is not retained. When transactions are synchronized to the
destination database, they are converted into a single record.
- Before you synchronize data, evaluate the impact of data synchronization on the performance
of the source and destination databases. We recommend that you synchronize data during
off-peak hours. During full data synchronization, DTS uses read and write resources
of the source and destination databases. This may increase the loads of the database
servers.
- During full data synchronization, concurrent INSERT operations cause fragmentation
in the collections of the destination database. After the full data synchronization
is complete, the storage usage of collections in the destination database is larger
than that of collections in the source database.
- During data synchronization, we recommend that you use only DTS to write data to the
destination database. This prevents data inconsistency between the source and destination
databases. If you use tools other than DTS to write data to the destination database,
data loss may occur in the destination database when you use Data Management (DMS)
to perform online DDL operations.
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| Special cases |
If the source database is a self-managed MongoDB database, take note of the following
limits:
- If you perform a primary/secondary switchover on the source database when the data
synchronization task is running, the task fails.
- DTS calculates synchronization latency based on the timestamp of the latest synchronized
data in the destination database and the current timestamp in the source database.
If no update operation is performed on the source database for a long time, the synchronization
latency may be inaccurate. If the latency of the synchronization task is too high,
you can perform an update operation on the source database to update the latency.
Note If you select an entire database as the object to synchronize, you can create a heartbeat.
The heartbeat is updated or receives data every second.
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