Comparing replicated data between instances in Instance Data Replication
- UpdatedFeb 1, 2024
- 3 minutes to read
- Washington DC
- Instance Data Replication
You can find missing or mismatched records by comparing replication data between instances in Instance Data Replication (IDR).
IDR synchronizes data between a producer instance and one or more consumer instances. After you activate a producer replication set and subscribe at least one consumer, you can send existing records from the producer to the consumer by seeding records. After seeding is finished, IDR maintains data synchronization between the instances by replicating new and changed records from the producer to the consumer.
If an insert fails on the consumer or when producer and consumer records don’t match after replication, you can use the data comparison feature in IDR to find these records and reseed them from the producer to the consumer.
Key benefits
- Identify records missing from the consumer instance after seeding.
- Identify mismatched records and view their differences.
- Keep data synchronized between instances by reseeding records.
Comparing transformed data
- The data comparison can return mixed results if records are added to a table on the producer and then a transformation replicates to a different table on the consumer instance.
- Mapped fields with different field definitions are skipped. For example, if a field on the producer has a different column type or column length than the mapped field on the consumer, the field is skipped.
- All fields that are modified by an adapter are skipped except for modifications made by the Task number adapter. For example, if a string is appended using the Concatenate String adapter, the data comparison can't undo the concatenation and compare the data using the original string, so the field is skipped.
Compatibility
Beginning in the Washington DC release, you can compare replicated data in bidirectional replication sets, discrete replication sets, and replication sets with transformations configured on either the producer or the consumer.
| Data comparison | Producer | Consumer | Supported replication sets |
|---|---|---|---|
| Producer to consumer | Washington DC or later | Utah and earlier | None |
| Producer to consumer | Washington DC or later | Vancouver | Supports unidirectional replication sets, but not the following:
|
| Producer to consumer | Washington DC or later | Washington DC or later | All replication sets |
| Data comparison | Consumer | Producer | Supported replication sets |
|---|---|---|---|
| Consumer to producer | Washington DC or later | Utah and earlier | None |
| Consumer to producer | Washington DC or later | Vancouver | Supports bidirectional replication sets, but not the following:
|
| Consumer to producer | Washington DC or later | Washington DC or later | All replication sets, but not unidirectional replication sets |
Limitations
- Journal fields are excluded from the comparison due to the potential size of their content.
- Attachments are not included in data comparisons.
- Sys Audit [sys_audit] table records are excluded from the comparison.
Related Content
- Deploying a replication configuration from one instance to another in Instance Data Replication
You can copy a replication configuration from one instance to another through an update set in Instance Data Replication (IDR).
- Cloning with Instance Data Replication
Ensure that certain tables are preserved or excluded to clone your database from one instance to another successfully with Instance Data Replication (IDR).
- Delays in replicating data with Instance Data Replication
Delays in replicating data from the producer instance to the consumer instance can occur with Instance Data Replication (IDR).
- Monitoring Instance Data Replication
You can monitor the status of active producer and consumer replication sets, scheduled jobs, seeding requests, and license or usage details through the Instance Data Replication (IDR) Monitoring Dashboard.
- Monitoring queues in Instance Data Replication
You can monitor the replication record queue, message produced queue, message consumed queue, and the messages processed for all replications sets through the Instance Data Replication (IDR) Queue Dashboard.
- Preventing insert and update errors in Instance Data Replication
You can prevent insert and update failures in Instance Data Replication (IDR) by specifying a class name filter in the producer replication set.
- Resolving data replication errors in Instance Data Replication
Resolve errors and monitor the status of Instance Data Replication (IDR) replication sets.